tenure after phd

Academic tenure: What it is and why it matters

Professor of English, Arizona State University

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George Justice is Principal of Dever Justice LLC, a higher education consulting firm.

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How would you like a job that was guaranteed and allowed you to do your work as you see fit and speak your mind with no repercussions? Most people would, and that’s the idea behind academic tenure. In the following Q&A, George Justice, an English professor and author of “ How to Be a Dean ,” explains the origin of tenure and the waning protections that it affords professors who have it.

What is academic tenure?

Of all the things a university professor can achieve in their career, few are as desirable as academic tenure. Academic tenure is a system of strong job protections that virtually guarantees a university professor will never be fired or let go except in the most extreme of circumstances. A key idea is to allow faculty to speak freely – whether on campus or in public – without fear of reprisal.

Achieving tenure is not easy or quick. First, aspiring professors must secure a “tenure track” position after excelling in a Ph.D. program, followed in many cases by one or more postdoctoral fellowships. Then, in a probationary period that can last from 5 to 10 years, but which typically takes 7 years , faculty must demonstrate academic excellence in teaching, research and service to the community.

The probationary period is then followed by a year-long process during which a professor’s work is evaluated by peer faculty – both inside and outside of the university where they teach – as well as administrators at their institution.

If they succeed in getting tenure, they can be promoted to the rank of “associate professor with tenure.” But if they are denied tenure, usually it means they have one more year to build up their credentials and find employment at another college or university – or leave academia altogether to find work in a different industry.

A little less than half of all full-time faculty at colleges and universities in the U.S. – 45.1% , or 375,286 according to 2019 data – have tenure.

When did tenure first appear?

The tenure system was created in the early 20th century as a partnership between the faculty and the institutions that employ them. Faculty came to be represented nationally by the American Association of University Professors, which was founded in 1915 by two of the era’s most famous intellectuals: John Dewey and Arthur O. Lovejoy . The association wasn’t a union, although now it does help faculty unionize.

In 1940, the association teamed up with the Association of American Colleges – now the Association of American Colleges and Universities – to define tenure as a system providing “ an indefinite appointment that can be terminated only for cause or under extraordinary circumstances such as financial exigency and program discontinuation.”

The real origins of the concept, though, lie in the practice of 19th-century German universities. Faculty in these universities created wide autonomy for their work on the basis of their pursuit of knowledge for its own sake . The greatest freedom and power went to those professors at the top of a rigid hierarchy.

In its 1915 “ Declaration of Principles ,” the association viewed faculty tenure as a property right and academic freedom as “essential to civilization.” “Academic freedom” includes rights both within and outside a professor’s daily work: “freedom of inquiry and research; freedom of teaching within the university or college; and freedom of extra-mural utterance and action.” The last of these means that faculty can speak up on matters of public concern outside of their specialized expertise without fear of losing their job.

Whom does it benefit?

As a job protection, tenure directly benefits college teachers. Indirectly, tenure benefits a society that thrives through the education and research that colleges and universities create .

The job protections are significant. Except in extreme circumstances, faculty who have achieved tenure can expect to be paid for teaching and research for as long as they hold their jobs. There is no retirement age. And colleges only very rarely go out of business.

Tenure’s benefits have weakened in recent years. Financially battered by the past year of COVID-19, institutions have let tenured faculty go merely with general assertions of financial stress rather than the deep crisis of “financial exigency.”

And termination “with cause” has evolved in recent years. For instance, federal law, including Title IX of the Federal Education Act , has pushed institutions to fire or force the resignation of faculty members who violate core principles of equal treatment, especially through sexual harassment of students.

Why is tenure controversial?

There are economic, political, ideological and social reasons why tenure has come under fire over the past 50 years .

From an economic perspective, higher education is big business with a big impact on the U.S. economy. State universities are among the biggest businesses. And some legislators believe universities should be treated simply like businesses. Professors would have no more job security than any other employees and could be fired without a rigorous process led by their faculty peers.

“What happens in our private sector should be applied to our universities as well,” argued Iowa State Senator Bradley Zaun , who introduced legislation that would eliminate tenure in his state’s public universities. The measure failed .

And in socially conservative parts of the country, legislators allege that professors have hypocritically violated students’ freedom of speech , including by interfering with their participation in conservative student political groups.

It’s not just from social conservatives. Colleges have suspended faculty members for using racial slurs that offend students. And faculty have sued the University of Arkansas over a revised tenure policy that would weaken protections when faculty challenge social norms.

What is its future?

Tenure continues to exist in American higher education, and surveyed provosts – the chief academic officers on their campuses – maintain support for retaining the tenure system on their campuses .

But those same academic leaders have hired increasing numbers of less expensive faculty without tenure over the past few decades.

In recent years, the percentage of tenured college teachers has fallen to 45.1% from nearly 65% in 1980 . Recent analysis suggests that if part-time faculty are included, a mere quarter of college teachers have tenure.

While research shows diverse faculty and peer viewpoints lead to a richer education for students , the tenured faculty are whiter and more male than the whole body of college teachers, let alone the U.S. population. Indeed, the tenured faculty has become demographically inconsistent with the students in their classrooms : 75% of college professors are white, whereas 51.1% of the population under 24 years old was non-Hispanic white in 2019.

Is the practice of academic freedom “essential to civilization”? Does it require tenure for faculty? Or is tenure a destructive job perk that limits innovation in an important service industry by entrenching faculty who may be mediocre and old-fashioned in their teaching and research? The one thing guaranteed in the future of tenure is that as long as it exists, it will continue to be controversial.

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Ph.D. students rethink the tenure track

The holy grail for ph.d. students has traditionally been a professorship at a prestigious university, the reward for years of rigorous research, frugal living and a hard-earned collection of published journal papers..

But in a sign of changing times, many Ph.D. students today are looking for jobs outside the halls of higher education, as tenure-track faculty positions at campuses nationwide become scarcer in a tight job market.

Enter “Beyond Academia,” the first career conference at the University of California, Berkeley, organized solely by Ph.D. students and postdoctoral fellows, an unlikely group for a non-academic job fair. The sold-out event — to be held in Berkeley this Friday, March 22 — is a quiet revolution if one considers the investment of time and money that goes into grooming a grad student for a tenure-track position.

“There are Ph.D. students who feel they can’t come out and say they want to leave academia, they’re too afraid,” said Els van der Helm, a fifth-year Ph.D. student in psychology and lead organizer of the conference. “This will give them a chance to explore other options. We have to start a conversation about this because academia is not for everyone.”

That said, there’s a risk involved for van der Helm, who is something of a wunderkind in sleep research, and other exceptional scholars: “Once you leave academia,” she said, “it can be hard to get back in.”

A changing career landscape, due to a divestment in higher education, among other things, is forcing a generation of graduate students, including many of UC Berkeley’s 5,800 Ph. D. students, to weigh the rewards of academia — job security, flexible schedules, travel, passion for one’s field — against perhaps better-paying and more accessible jobs in corporate, government and nonprofit sectors.

A study published last year in the journal Science suggests only 20 percent of U.S. graduate students in science, technology, engineering and mathematics will land a tenure-track position within four to six years of completing a Ph.D. Meanwhile, the National Science Foundation reported that in 2009, nearly 50,000 students earned Ph.D.s in America, the highest number ever recorded. And, between 2005 and 2009, American universities conferred 100,000 doctoral degrees, but only 16,000 new professorships, according to the 2010 book “Higher Education?”

That noted, the percentage of UC Berkeley doctoral students landing a tenured faculty position is much higher (57 percent) than the national average of 41 percent.

“Our data show an enormous range of career trajectories our doctoral degree recipients have followed in the past,” said Andrew Szeri, dean of the Graduate Division and a professor of mechanical engineering. “I certainly don’t expect the future to be different in this respect. What can be different is that we can be better prepared to present a more balanced view of where people go after earning their degrees.”

As for the “Beyond Academia” conference, at which Szeri will be introducing keynote speaker Marty Nemko, a career coach and author, he added: “It makes good sense to consider the full range of possibilities as you near completion of your degree. I certainly did — and learned a lot in the process about what I really wanted to do.”

More than half of UC Berkeley’s 10,000 or so graduate students are in doctoral programs, and 23 percent of those are in engineering. Other popular doctoral programs, in order of their preference by students, are mathematics, the physical sciences, the social sciences and education. A survey by UC Berkeley’s Career Center of students who graduated with Ph.D.s between 2007 and 2009 shows that 56 percent got jobs in academia,  with 34 percent of them in tenure-track positions, 45 percent in post-doctoral appointments and 10 percent in non-tenure track faculty posts.

Van der Helm, a native of the Netherlands, started contemplating her career prospects last summer after presenting research at prestigious conferences in China and Japan. After coming down from that adrenalin high, she took an online “Strengths Finder” test to help determine her career path and found that her talents were just as well, if not more, suited to non-academic jobs. In the fall, she took UC Berkeley education professor Michael Ranney’s course, “Getting Your Doctorate and Getting a Good Job,” where she met others who shared similar career concerns, and they formed a group.

Among them was Bryan Alvarez, a seventh-year doctoral student in psychology who had been conducting campus life surveys and hosting “Grad Anon” support groups at UC Berkeley that delved into career concerns. When van der Helm, whom he knew, contacted him with her conference idea, he jumped right in, knowing the climate was perfect for an event of this scale.

“The interest is just phenomenal,” said Alvarez. “The number of Ph.D.s is rising exponentially and everyone’s connecting through social media, so conversations are happening online and elsewhere about how to best use our skill sets.”

Last November, the group sent out an online career survey to their UC Berkeley peers in psychology, neuroscience and cognitive science. In one week, they received 92 responses. The survey quickly wended its way to other graduate student groups in chemistry, physics, education and other departments, and it soon became clear that respondents were hungry for information about jobs in technology, consulting, K-12 teaching, think tanks and other non-academic workplaces.

Since then, 230 UC Berkeley graduate students have signed up for this week’s “Beyond Academia” conference, whose sponsors include the psychology, vision science, cognitive science and linguistics departments at UC Berkeley, as well as the Helen Wills Neuroscience Institute, the Graduate Assembly and the Associated Students of the University of California.

Panelists will include Google statistician Rehan Khan; Facebook researcher Flavio Oliveira; Insight Data Science founder Jake Klamka; Jodi Davenport, senior project director of WestEd, which uses research to improve education; Elizabeth Iorns, CEO of the Science Exchange online marketplace and Sandra Aamodt, a science writer and former editor in chief of Nature Neuroscience.

“A lot of the speakers told us, ‘I wish I’d had a conference like this when I was in college. It would have made my search so much easier,’” said Ian Cameron, a UC Berkeley postdoctoral fellow in neuroscience and president of the Berkeley Postdoctoral Association.

A Canadian citizen, Cameron applied for about 10 jobs in academia and got one interview, which landed him a post as a senior researcher at the Donders Institute in the Netherlands.

“I really do like academia, and I’m on a track to stay in it,” Cameron said. But he says he would also have been thrilled to land a research or policy job in government or nonprofit sectors: “I want to be involved in building something, whether it’s building a lab or building a program at a think tank or a nonprofit,” he said.

Mariana Garcia, a fifth-year doctoral student in vision science and a member of the conference leadership team, also hasn’t ruled out academia: “I just want a job that I’m excited to go to every day, a job that isn’t meaningless, where I’m making a difference,” she said.

Alison Miller Singley, a second-year doctoral student in psychology, left the corporate world for academia and is looking for a job that combines both: “My fantasy job would be translating research into the development of education tools, which I could accomplish in academia or out,” she said.

While the conference leadership team’s career goals and experiences differ widely, they all agree that in the current climate, Ph.D. students need a lot more options, and that the “Beyond Academia” conference should be an annual event.

“We’re not saying, ‘Don’t stay in academia,’” van der Helm said. “We’re saying, ‘If you pick academia, know what you’re not picking. Take a break. Look around.’”

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Research Article

Postdocs’ advice on pursuing a research career in academia: A qualitative analysis of free-text survey responses

Roles Data curation, Formal analysis, Writing – original draft, Writing – review & editing

Affiliation Hunter College, City University of New York, New York City, NY, United States of America

Roles Formal analysis, Methodology

Roles Formal analysis

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Epidemiology and Biostatistics, SUNY Downstate Health Sciences University, Brooklyn, NY, United States of America

• Suwaiba Afonja, 
• Damonie G. Salmon, 
• Shadelia I. Quailey, 
• W. Marcus Lambert

• Published: May 6, 2021
• https://doi.org/10.1371/journal.pone.0250662
• Peer Review
• Reader Comments

The decision of whether to pursue a tenure-track faculty position has become increasingly difficult for undergraduate, graduate, and postdoctoral trainees considering a career in research. Trainees express concerns over job availability, financial insecurity, and other perceived challenges associated with pursuing an academic position.

To help further elucidate the benefits, challenges, and strategies for pursuing an academic career, a diverse sample of postdoctoral scholars (“postdocs”) from across the United States were asked to provide advice on pursuing a research career in academia in response to an open-ended survey question. 994 responses were qualitatively analyzed using both content and thematic analyses. 177 unique codes, 20 categories, and 10 subthemes emerged from the data and were generalized into two thematic areas: Life in Academia and Strategies for Success .

On life in academia, postdoc respondents overwhelmingly agree that academia is most rewarding when you are truly passionate about scientific research and discovery. ‘Passion’ emerged as the most frequently cited code, referenced 189 times. Financial insecurity, work-life balance, securing grant funding, academic politics, and a competitive job market emerged as challenges of academic research. The survey respondents note that while passion and hard work are necessary, they are not always sufficient to overcome these challenges. The postdocs encourage trainees to be realistic about career expectations and to prepare broadly for career paths that align with their interests, skills, and values. Strategies recommended for perseverance include periodic self-reflection, mental health support, and carefully selecting mentors.

Conclusions

For early-career scientists along the training continuum, this advice deserves critical reflection before committing to an academic research career. For advisors and institutions, this work provides a unique perspective from postdoctoral scholars on elements of the academic training path that can be improved to increase retention, career satisfaction, and preparation for the scientific workforce.

Citation: Afonja S, Salmon DG, Quailey SI, Lambert WM (2021) Postdocs’ advice on pursuing a research career in academia: A qualitative analysis of free-text survey responses. PLoS ONE 16(5): e0250662. https://doi.org/10.1371/journal.pone.0250662

Editor: Frederick Grinnell, University of Texas Southwestern Medical Center at Dallas, UNITED STATES

Received: December 24, 2020; Accepted: April 8, 2021; Published: May 6, 2021

Copyright: © 2021 Afonja et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: WML acknowledges support by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR002384. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Postdoctoral researchers (“postdocs”) seeking research faculty positions are facing increasing challenges in their career pursuits [ 1 – 5 ]. The first and most dynamic is the large number of postdocs competing for a limited number of faculty positions. In the early 1970s, the number of NIH principal investigators (PIs) was equivalent to the number of biomedical postdocs and exceeded the number of graduate student researchers by more than 50% [ 6 ]. Growing from 7,000 to over 21,000 biomedical postdocs today, some argue that there is an oversupply of postdocs and overemphasis of academic tracks, leading to a hypercompetitive culture among trainees for faculty positions [ 7 , 8 ]. This oversaturation may be partially attributed to insufficient preparation of graduate students for career options outside of academia [ 9 – 12 ], leaving postdoctoral positions as a default career step for many PhD holders [ 13 , 14 ]. Others maintain that postdoc oversaturation is a misperception as postdoc positions should not be considered only as preparation for an academic job but rather as an opportunity for skill development for a multitude of fields [ 10 , 15 – 20 ]. In addition, the total number of tenure-track faculty positions has remained relatively constant over the past few decades, and the disparity between postdoctoral appointments and available tenure-track positions has not been proportionally adjusted for [ 6 , 7 , 21 ]. Currently, tenure-track faculty positions only represent approximately 15% of postdoc career outcomes [ 22 ].

Second among these growing challenges is the poor sense of financial security felt by many postdoctoral researchers. Previous reports note low salaries and a long overall training length for many postdocs [ 22 , 23 ]. The postdoctoral position, intended to be a temporary training period, has been increasing in length without a substantial increase in pay, with recent studies reporting postdocs completing more than one postdoc [ 24 , 25 ]. McConnell et al. [ 22 ] found that postdoctoral salaries are not maintaining parity with the cost of living increases. At the time of their study (2016), postdocs reported salaries in the range of $39,000–$55,000 (median $43,750, mean $46,988) [ 22 ]. The financial sacrifices and increasing time commitment made during this training phase are compounded by a lengthy biomedical doctoral training period with a median time to degree of greater than 5 years [ 26 ].

Over the last five years, the National Institutes of Health have increased the Ruth L. Kirschstein National Research Service Award (NRSA) stipends by four to five percent on average for postdocs [ 27 ]. This adjustment is consistent with recommendations from the 2012 Biomedical Research Workforce Working Group report from the NIH and the 2018 Next Generation of Biomedical and Behavioral Sciences Researchers : Breaking Through report from the National Academies of Science, Engineering, and Medicine [ 27 – 29 ]. Many institutions are starting to follow suit, either using the NRSA levels as guidelines for setting postdoctoral salaries or setting the minimum in accordance with the Fair Labor Standards Act [ 30 ]. Historically low stipends and a sense of financial insecurity are associated with increased interest in non-academic careers [ 25 ].

Researchers who begin a postdoctoral position despite awareness of the salary support and limited availability of faculty positions may still lose interest as their training progresses [ 31 , 32 ]. Some evidence suggests this is due to the incompatibility between their career preferences and the demands of the academic lifestyle [ 9 , 33 ]. Unrealistic expectations or lack of knowledge about aspects of academic life such as academic freedom, administrative obligations, funding, and the time commitment may cause many to prematurely abandon this track despite already committing a significant number of years to it [ 33 ]. With regard to women and underrepresented minority (URM) postdocs, the largest exit from the academic research pipeline can be observed in the first two years of postdoctoral training [ 25 ]. An increase in transparency about life in academia and the dissemination of more information on the critical steps for securing an academic research position should increase the retention of trainees by giving those who choose to commit to this track, despite the known challenges, the opportunity to make well-informed career decisions that reflect their personal and professional values [ 34 ].

Postdoctoral researchers can provide a unique perspective on the benefits and challenges of a research career. They are in a distinctive training period that serves as the branch point for their future careers and have personally experienced many of these benefits and challenges. Our previous work identified the most influential factors for those who intend to pursue teaching or non-academic career paths (this includes teaching-intensive faculty positions, non-academic research positions such as industry, non-research but science-related positions, and non-science related positions) [ 25 ]. Job prospects , financial security , responsibility to family , and mentorship from their PI were the most cited reasons for those opting for careers outside of academia [ 25 ]. Postdocs who pursue academic research careers produced significantly more publications (9 vs. 7, p<0.001), more first-author publications (4 vs. 3, p<0.001), and have a higher first-author publication rate (0.56 vs. 0.42, p<0.001), yet, a significant portion (40%) of even the most productive postdocs opt out of pursuing an academic career [ 25 ]. Thus, a greater understanding of how postdocs perceive the path to academic research independence is warranted. In addition, strategies to overcome the challenges faced along the way are also needed.

This current study amasses the guidance and recommendations of 994 postdocs on pursuing an academic career. Our objectives are:

• To understand how postdoctoral research trainees perceive the benefits and challenges of pursuing an academic research career;
• To provide ways to overcome these challenges.

The advice gathered from the postdoctoral researchers in this study will help prospective trainees make more informed career decisions. Instead of only describing some of the obstacles they have faced, the postdocs provide numerous strategies and suggestions to help future and current researchers take greater control of their career outcomes. These primary accounts further elucidate many of the challenges researchers encounter when choosing career paths. Therefore, such disclosure can increase transparency about the benefits and challenges of pursuing a tenure-track faculty position and encourage a more efficient transition from training stages to careers across the scientific workforce.

U-MARC survey

Postdoctoral scholars (“postdocs”) in the biological and biomedical sciences from across the United States were invited to complete an original survey instrument entitled U-MARC (Understanding Motivations for Academic Research Careers) in July of 2017. The 70-item survey (1) measures views on determinants of career choice in science and (2) measures outcome expectations and self-efficacy around research careers using two original scales. The study’s theoretical framework was derived from (i) Social Cognitive Career Theory which states that self-efficacy, outcome expectations, and personal goals affect career decision and (ii) Vroom’s Expectancy Theory which infers that motivation is a result of how much an individual wants a reward (valence), the probability that a specific effort will lead to the expected performance (expectancy), and the belief that the performance will lead to the reward (instrumentality) [ 35 , 36 ]. We used expectancy theory to build an outcome expectations instrument in the U-MARC survey, with some items taken from the Research Outcome Expectations Questions (ROEQ) [ 37 ]. For full details on the development of the U-MARC survey instrument, refer to our previous work (Lambert et al.) [ 25 ].

Data analysis

In this study, we qualitatively coded 994 survey responses to an open-ended question from the U-MARC survey using hallmarks of both content analysis (examining patterns in text, highlighting frequency counts) and thematic analysis (interpreting themes within the data). The question states: “What advice would you give to someone thinking about an academic research career?” Two researchers were involved in the coding process, each independently deriving codes. A process of open, axial, and then selective coding was followed by generally coding and discussing major concepts, categories, and themes. A third researcher was consulted to help determine crosscutting themes and recurrent patterns, in consideration of analytic connectedness. We repeated this cycle until we achieved thematic saturation, and novel themes stopped emerging from the data. NVivo 12, a qualitative transcript software, was used to assist with the coding of the data.

Throughout the manuscript, we include transcript numbers corresponding to the survey respondents’ answers so readers can differentiate between the sources of any given set of quotations. The full list of responses and derived codes are included in the S1 Table .

Data collection and sampling method

All work was conducted under the approval of the Weill Cornell Medical College Institutional Review Board (IRB# 1612017849), and all respondents self-selected and provided consent for participation in the study. A purposeful sampling strategy where participants were recruited through postdoctoral listservs from top-ranked research universities and institutions was used instead of snowball sampling, where existing participants would have recruited other potential candidates from their networks. All survey respondents self-selected to participate in the survey based on the inclusion and exclusion criteria previously published [ 25 ]. The sample represents wide geographic (over 80 universities) and subfield diversity. The number of institutions and the percentage of respondents from each institution were published in supplementary file 2 of our previous publication [ 25 ]. We also determined the percentage of respondents from highly-ranked life science research institutions in the US based on counts of high-quality research outputs between January 1, 2017 and December 31, 2017 according to rankings from Nature Index ( Fig 1 - figure supplement 1D) [ 25 ]. The majority of respondents are from highly-ranked US institutions, but the differences in institutional ranking do not fully account for the differences in career intention [ 25 ]. It should also be noted that postdoctoral appointees at the top 100 institutions in the United States (n = 56,092) account for approximately 88% of the total number of postdocs in the country (n = 63,861) [ 38 ]. From the total sample of participants who completed the U-MARC survey (n = 1248), only respondents who identified as a postdoctoral scholar or research associate were included in this analysis (n = 994). The sample postdoc participant pool represents 6% of the total amount (21,781) of appointed biomedical and biological postdocs the year the survey was conducted (2017) according to the National Science Foundation. The REDCap electronic data capture tool was used to collect and manage the 70-item anonymous U-MARC survey instrument. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies.

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(A) To estimate the prevalence of advice from postdoc respondents, the frequency of the codes was analyzed and displayed by the bars (left axis) in descending order along with its contribution to the cumulative percentage, represented by the line (right axis). (B) The top 20 most frequent codes are displayed and (C) listed by frequency.

https://doi.org/10.1371/journal.pone.0250662.g001

To establish a representative framework of life in academia at the postdoctoral stage of training and gather recommendations for success in this field, we asked postdoctoral candidates, “What advice would you give someone thinking about an academic research career?” The sample of 994 postdoctoral researchers included US citizens (n = 557, 56%), international fellows (n = 434, 44%), female postdocs (n = 615, 62%), male postdocs (n = 378, 38%), and underrepresented minorities (URM) postdocs (n = 174, 13%) ( Table 1 ). URM postdocs include the racial and ethnic categories of American Indian or Alaska Native, Black or African American, Native Hawaiian or other Pacific Islander, and/or Hispanic or Latino. The participants responded similarly across gender, race/ethnicity, and national status. The average time reported to earn a PhD in the biological or biomedical sciences for the postdoctoral respondents was 4.6 years, with an additional 2.7 years spent in postdoctoral training. The average time to PhD recorded here is lower than that of the national average due to the inclusion of the international students’ shorter doctoral training lengths.

https://doi.org/10.1371/journal.pone.0250662.t001

With the information gathered from the 994 responses, 177 codes and 20 categories emerged. To estimate the prevalence of advice across postdoc respondents, we determined the frequency by which each code was cited ( Fig 1A ). ‘Passion’ emerged as the most frequently cited code, referenced 189 times across 994 responses, more than twice the amount of other codes ( Fig 1B ). The top 20 most frequently cited codes included: hard work, self-reflect, strong mentorship, don’t go into academia, financial stability, need for funding, consider career alternatives, perseverance, explore all options, research before committing, long-term commitment, grantsmanship, need for publications, sacrifice, network, choose the right laboratory, work-life balance, luck, and backup plan ( Fig 1C ). In the following text, we summarize the postdoc respondents’ advice across two major themes: Life in Academia and Strategies for Success .

Life in academia

Academia is a lifestyle..

According to the surveyed postdocs, a career in academia is not merely an occupation; it is a lifestyle ( Table 2 ). The postdocs express that the time and commitment required for success in academia often shapes a researcher’s personal, professional, and social life:

…anyone who pursues a research career has to be [prepared to] work in a high-pressure environment that consumes your life. There is really no separation between your research and life. You must be prepared to sacrifice holidays and special occasions with your family. (379)

https://doi.org/10.1371/journal.pone.0250662.t002

So, the postdocs advise performing a self-assessment of your values and priorities to determine whether this career can satisfy your personal and professional needs:

Consider what balance of work and personal time is acceptable and will make you happy. Those who reliably and regularly receive high impact publications and large grants tend to spend a majority of their time in lab writing, and have less free time outside [of the] lab. (157) Set the professional goals you are willing to achieve without endangering your personal life. (197)

Respondents describe the challenges they face as postdoctoral researchers to also include long hours, a demanding workload, unanticipated setbacks, a competitive funding and research climate, and delayed gratification, consistent with other studies [ 5 ]:

Academic research is great if you enjoy working hard, tolerate frustration, and accept that sometimes you need to work for years before seeing results. It’s not that great if making money is important for you, if you need a lot of free time for your non-work life, and if you need frequent reinforcement and sense of success. (17)

The trade-offs to these challenges include scientific creativity, problem solving, academic freedom, and travel. Academic freedom was cited as one of the main benefits of pursuing an academic research career:

If making discoveries on a day to day basis, big or small, is what you crave for then [this] is the career. If you have the patience to go through failure or unexpected results to find something new and interpret it, be criticized without giving up and then prove your point then this [is] the career. If you are curious enough to get to the truth, no matter what but at your own pace then this is the career. (427) Be prepared for a lot of freedom in thought and ability to pursue academic interests with a great deal of effort in lab management, grant writing, and grant management. (75)

Many also note that luck (or probability) plays a significant role in your success in experiments, publications, funding, and job opportunities. This perception has been previously linked to levels of outcome expectations among postdocs, i.e., whether their hard work leads to high performance [ 27 ]:

You can put in 80 hours a week, but unless you get lucky, you will not be able to publish in multiple high impact journals in order to attain a position in Academia. The hyper competitive climate in science is extremely discouraging to intelligent and innovative minds… (951)

However, several caution against allowing your research success to define you:

Do not base your sense of self-worth on having an academic position. Give it your best shot, but there are many viable pathways out there and you shouldn’t feel that being an academic is the only viable option. (186)

Overall, the postdocs describe life in academia as one characterized by significant time demands for conducting research and fulfilling other responsibilities. They note the importance of establishing a healthy work-life balance and advise prospective researchers to determine whether their fields of interest can meet their personal and professional expectations.

Postdocs feel underpaid and undervalued.

Several survey respondents indicate that compensation at the postdoctoral level is unsatisfactory:

Relative to their educational attainment and training, postdocs are very poorly paid, and there is little or no job security. (199) …academic institutions arbitrarily devalue your contributions both financially and through the game of non-promotion. (835)

Many call prospective candidates to be aware of these financial challenges:

Can you live with a salary of 20k-30k as a graduate student until you are 30? Are you ready to start a family with a salary of 50k as a postdoc when your friends are making 70k-80k without a PhD? (979)

However, the postdocs indicate that passion should be the primary motivation for those interested in pursuing an academic career, not financial gain:

If you care about money, don’t come. This field is sustained only by passion now. (448) Science should be your number one passion. It must be strong enough to overlook the many long hours and the fact that you’re spending your peak earning potential years in a stressful, low-pay, unstable ’training’ position. (736)

Though several postdocs feel many institutions fail to provide the level of professional development, career placement, and employee benefits to postdocs as given to students or faculty [ 39 , 40 ]. These limited job prospects lead to feelings of not being appreciated in postdoc positions [ 41 ]:

You will be mentally run-down, under-paid, under-appreciated, and in the end make less than you’re worth with fewer benefits. (732) I don’t want my kids to go into research; I want them to do something where their work and knowledge is actually appreciated. And where this appreciation is reflected in the salary. (693)

So, many highly recommend being proactive about choosing the best work environment to complete your postdoctoral training:

…environment matters. Being at a supportive institution with excellent mentorship and opportunities in your field of choice will be important for success. (777) Have a strong mentor and support system at your institution because your institutional resources will be heavily counted toward successfully obtaining a grant. (367) Make sure to choose a lab that publishes regularly and a mentor who will actually act as a mentor and not just get science out of you. (594)

The postdoctoral researchers find that the state of funding in academia has made it difficult to not only support their research but also their personal cost of living. However, they find that if you are passionate about your work and can find a supportive institution with strong mentorship, those sacrifices can be reduced and are ultimately worth the effort.

Strategies for Success

Prepare for multiple career paths..

Some postdocs do not recommend pursuing an academic research career at this time. Despite hard work and considerable sacrifice, the probability of obtaining a tenure-track faculty position and financial insecurity were cited as the main deterrents for pursuing an academic research career:

Do something else. I am a successful young research scientist, but I would not advise a student to pursue a career in academic research. The balance between the effort put in, and the benefits gained is completely skewed. Dedication and hard work are no guarantee of success in terms [of] publications. Very often, early career decisions as to the lab you apply to, to do your PhD training, have an inordinate influence in your career. Also, mentors have an inordinate influence in their [students’] happiness and success… (199) I just started to apply for tenure-track openings and have been told by dept. chairs that I need to have funding (K-award) in hand to be seriously considered for a position. I have 30+ publications and received my own funding since I was a graduate student (NIH F31 & F32 plus over $120K in supplemental funding). My K-award is currently under revision and feel my future is currently 100% dependent on my whether I get a K regardless of what is on my CV or my past accomplishments. (238)

In consideration of these challenges, several postdocs indicate that there are many other viable career opportunities for researchers. They also suggest that academic research careers should be framed as a part of a myriad of successful post-PhD careers, rather than an alternative to those unsuccessful at achieving a faculty position:

Please, don’t consider [an academic research career] as the only respectable career for a scientist. Keep your options open. (474) I think the PhD is still a worthy goal. But I’ve come to realize the faculty position isn’t the be all and end all of the process. There are many other useful and creative and important ways to use a [PhD] degree. I think new generations are coming around to that: they embrace alternative careers and they are being trained for them in better ways as universities accept the fact that most of us don’t attain the faculty job… Another thing is, if you get the [PhD] and you want to leave academia, make a plan for that career- don’t get sucked into a postdoc when you [don’t] want to become a PI. (390) If you can succeed in basic research, you can be more successful in industrial, financial or other [fields]. (446)

Some of the postdocs recommend exploring multiple career options immediately, while others encourage keeping an open mind about multiple career paths in case the academic track becomes less viable ( Table 3 ). Pursuing a career in industry was the most cited career choice outside of academia by the postdoc respondents because of its competitive salaries, structured career advancement, better work-life balance, and the opportunity to continue scientific research or make contributions in other capacities.

https://doi.org/10.1371/journal.pone.0250662.t003

Reflect on your motivation.

Passion, coupled with resilience, was cited as the primary driving force for pursuing an academic research career:

Be sure you are passionate about your field of [study] and are pursuing the career for the right reasons, because it is not an easy career path. It allows for creativity, flexibility, and joys of learning and discovery, but is challenging in terms of funding, navigating bureaucracy and politics, administrative obligations, etc. (101)

The postdocs assert that researchers should not be driven by extrinsic factors such as wealth or fame:

People that are successful in the academic field are not in it for the money or fame. Chances are you won’t become famous or rich, but you do have the potential to help countless amounts of people, and if you are passionate about research and helping others, you shouldn’t let the troubles of funding or the woes of others deter you from your goals. (415) Never forget that the goal of biomedical research is to eventually find targets for human health issues that will hopefully help eradicate disease… and that research does not occur in a vacuum and requires passion, leadership, hard-work, and collaboration. (635)

Many of the respondents described the absence of passion as one of the leading causes for abandoning the pursuit of an academic research career. They maintain that love for the sciences and the impact of academic research is what makes the sacrifices worthwhile.

Assess readiness.

To supplement this advice, the postdocs define the qualities of a good scientist:

…true scientists care very little about money or taking the easy route. They are just intellectually curious and looking for answers to their questions. (77) Make sure you really enjoy coming up with your own hypotheses, have the knowledge to assess their novelty, and the writing skills to get them funded. (613) [Researchers’] daily tasks rely on numerous skills like writing communication, teamwork, problem solving, planning, learning, self-criticism, etc. (730)

According to the respondents, good scientists are passionate researchers who conduct thorough scientific investigations, demonstrate resilience in the face of difficulty, and are disciplined leaders in their fields. They are confident, excellent collaborators, and comfortable with failure and uncertainty. Their ability to take criticism and recover from setbacks allows them to overcome rejection and persevere through the many challenges present on this track:

Doing good science is slow and hard, and there are many times in research that it is easy to get discouraged—make sure you identify a way to reignite your passion for research so that you can overcome those times of frustration—we need more people and more diverse ideas in this profession, not fewer. (210)

Based on these qualities, the postdocs call prospective researchers to assess their strengths and weaknesses to determine if they are well-suited for this profession:

Do you truly enjoy research and the responsibilities (i.e. writing papers/grants) that come with those responsibilities? Are you competitive and confident in your ability to do science? Are you able to compartmentalize when research fails and not place blame on yourself? (206) There is always someone smarter out there, but you can control how hard you work. Research, like many things in life, is a battle of attrition. Work hard in the lab, write a lot… .like more than you think you should, read often, collaborate with others, keep growing. And most importantly, don’t let a paper or grant rejection define you. Your worth is derived from the things in your control, not the things out of your control. (798)

The postdocs recommend performing an honest self-assessment of your motivations and abilities to determine whether you have the drive and character necessary to maximize your chances at successfully obtaining a tenure-track faculty position.

Be strategic.

The postdocs emphasize the importance of being diligent and methodical about career development:

Pursuing science for the sake of exploring how the world around us works, and planning an academic research career are two very different endeavors, which require many mutually exclusive skills. Working towards a career in science must include careful choice of mentors, labs and projects in graduate school and post-doc. (714)

They also advise strengthening your research skills, staying informed about current research, and finding a supportive community to grow and develop in:

Learn how to critically read data and develop independent ideas and experiments. Work hard both at the bench and at understanding and staying current in the literature. Learn to ask for help and take criticism. Build your professional network to include [scientists] of various backgrounds and expertise. Meet and discuss your science as [frequently] as possible with these colleagues. (568)

The following sections expand on these strategies for success ( Table 4 ).

https://doi.org/10.1371/journal.pone.0250662.t004

Choose the right laboratory.

The postdocs stress that your choice of laboratory is one of the most critical steps for career advancement:

Find a lab that has [a] track record of postdocs transitioning to professorships. Your postdoc boss has the most influence on your own independent academic career. [It’s] all about mentorship. (279) Do intensive research, not only about the area you’re interested in, but the environment/morale of the lab itself before taking a job in a lab. (175)

The postdocs recommend carefully assessing all aspects of the laboratory environment before committing to a mentor or laboratory. This might involve conducting informational interviews to gain insight into your potential work environment, the laboratory’s publication record, and your prospective PI’s expectations of you. Due to your PI’s influence on your future, many advise assessing mentorship compatibility before committing to a laboratory to ensure that your values and expectations are compatible.

Choose mentors wisely.

The postdocs strongly emphasize the importance of strong mentorship on career growth:

Find a mentor who has the time and passion to see [you] grow and is willing to explain what the different career trajectories are, how you go about finding them, and wants to assist you in that journey. You need to find a mentor who values your potential as a future scientist and doesn’t just view you as cheap labor. (282) The greatest component to my success thus far has been asking the right people for help with grants, experiments, and other challenges. Without the support of my community it would be difficult to push forward research initiatives and secure funding for them. (31)

The postdocs share that insufficient support from PIs may leave researchers underdeveloped in some critical academic skills. So, they highly recommend seeking out multiple mentors at various stages of their careers because these professionals offer invaluable perspectives, skill sets, advice, and resources.

Publication strategies to consider.

Although there is debate about the significance of journal impact factor, there is certainty among the postdocs about the need for publications to become established in the academic community:

[Academia is] not a meritocracy. Either you have to publish a lot, or publish in high impact journals only. (515) Papers are the currency of research, so it is crucial to publish extensively in reputed journals. In the job market, being able to market your ’brand’ of science—topics, approach, methods, [etc.] becomes an important ingredient to success. (714)

Many recommend strengthening your research and writing skills to maximize grant and publication success:

Develop your brainstorming/project design skills. The opportunities to do that as a postdoc may be slim, but it is essential to being able to write your own grants and secure independent funding. (172) I would recommend that they try to be as independent as they can in their research ideas, strategies and grant writing (from Grad school and on). If they are successful at each of these, and their ideas are well perceived by their field, then they likely have a shot. It is important to think about what you bring to the field and what you want to teach others through your research and mentoring. (405)

They also advise assessing the publication record of the laboratory you are considering before committing to it:

For grad school and postdoc [choose] labs where the PI is established in his field because this is the way to get published in high ranking journals and to get your grants approved, without which you cannot develop a long-lasting career in Academia. (312) Get the training from the lab [with a] history of publishing top journals. Name of the school is not as important as the quality of the paper your candidate lab publishes. (330)

Some suggest working on various projects to enhance your academic record:

…do not only work on one project, but several, if you work on a risky project, get a second safer project to ensure you get regular publications… (25) Having a diverse portfolio helps, rather than one big project, one big book, or one big paper in the pipeline. I built my pipeline very slowly, and that gave me stress. I do think there is a need to step outside the publish or perish game, and craft one’s own rules of engagement if possible. One way to do this is possibly doing work meaningful to oneself rather than looking at where the funding comes from, or what everyone else is doing. (891)

The postdocs highlight the importance of publishing because it gives your research exposure, builds your credibility within the scientific community, and increases your competitiveness for an academic research position.

The postdocs find networking to be an essential component of success in academia:

[Networking] with peers and labs you’re interested in and offering your help or services or forming collaborations provides vital long-lasting and fruitful connections. [It’s] often who you know that counts in terms of publications. [Get] involved with excellent research labs, learn from them and become a vital part of the team. (518) Go outside your comfort zone of the lab, engage in science outreach, network, interact! Science is more than working hard at the bench, and I wish somebody had told me that earlier in my career. (685)

The postdocs recommend attending conferences, building connections, and collaborating with others because those are important ways to develop relationships with scientists throughout the community, learn from their expertise, find mentors, and share your own research and ideas.

Overall, the postdocs’ provided these recommendations to help prospective researchers make more informed decisions about their research career pursuits:

In order to achieve a successful career in academic research, one needs to understand early enough that it is more than a job in science—it a permanent dedication to scientific topics, with a lot of workload for a single person. Persistence and patience are essential traits to succeed. (469)

In this manuscript, we present the advice of 994 postdocs on pursuing an academic research career. The postdocs’ responses were analyzed to derive codes that encapsulated the major concepts being discussed. We found 177 distinct codes in 20 categories across 10 subthemes and two broad themes. In the first theme, Life in Academia , postdocs detail a picture of academic life from the point of view of the trainee, not often captured in the literature. According to several studies, the postdoctoral experience in the United States has not been captured comprehensively in more than a decade [ 7 , 22 ]. This scarcity of data negatively impacts postdoc career outcomes and the overall vitality of the scientific workforce.

In this study, postdocs highlight both the flexibility and challenges of academic life: “It allows for creativity, flexibility, and joys of learning and discovery, but is challenging in terms of funding, navigating bureaucracy and politics, administrative obligations, etc.” They also report that this track demands a significant commitment to seeking funding and publishing research, typically exceeding normal work hours. Thus, for many postdocs becoming a faculty member would fulfill their passion for research and discovery, but success requires managing the constant tension between work demands and their personal lives. Before committing to this career path, one has to decide if the lifestyle and its challenges are worth the reward.

One major challenge that the postdocs frequently referenced in this study was financial insecurity. We suspect that not everyone considers the financial impact of years of training until they are immersed in it. In this study, we find postdocs’ frustrations over aspects of financial support. Some postdocs advised not pursuing this path unless you come from a wealthy family. Others were very specific about the personal cost of this education and training: “…I’m in my mid 30’s and have worked 60+ hours a week for 10+ years for essentially minimum wage in hopes of getting an academic position.” Such openness is needed to help future trainees have a clearer understanding of the challenges in the field and help funding agencies understand how to improve access for all trainees. Choosing to pursue an academic career should not be dependent upon how long one can sacrifice financial stability and security. Postdocs should not be driven away from academic paths because they do not have the financial means to complete a postdoc.

The increasing length of this poorly funded training period with no guarantee of success causes financial instability and job insecurity [ 22 ]. Moreover, the increasing age for establishing scientific independence also translates into why there is a limited availability of faculty positions. Zimmerman shares that the reported average age for scientists to secure their first NIH grant is 42 [ 7 ]. This data along with the fact that the number of tenure-track faculty positions has remained consistent over the past few decades may in part account for the shortage of available positions as more senior researchers maintain their tenure to reap the benefits of the personal, professional, and financial challenges they have endured [ 7 , 21 ].

In our second theme, Strategies for Success , postdocs provide recommendations for maximizing the potential for success in achieving an academic research career. The postdocs overwhelmingly emphasize the importance of possessing a strong love and passion for science. The current literature does not capture this emphasis on passion for success. ‘Passion’ being the most frequently cited code in this paper, referenced 189 times, highlights the weight of intrinsic values in the supposed impersonal scientific world. As previously mentioned, one respondent shared that “this field is sustained only by passion now.” For many, passion is absolutely key for longevity in the field. A unique category that emerged under this theme of passion was characterized by a caution in letting happiness or self-worth depend on scientific research or obtaining an academic position. One postdoc noted: “Don’t make your happiness depend on your academic research career.” Similarly, another noted: “Do not base your sense of self-worth on having an academic position.”

Under our second major theme, the postdocs also expressed frustration about several other aspects of the field. A portion of them adamantly discouraged pursuing academia. Their responses confirm previous reports showing that the current state of academia is underscored by hypercompetitive climates, poor sense of financial security, and a perceived shrink in available tenure-track faculty positions [ 22 , 25 , 42 ]. One postdoc stated, “Put it this way, even if you are in a top Ivy League school you still need a mentor who will fight for you (I see my supervisor who is an MD/PhD every 4 weeks or so, left to troubleshoot alone), a lab that is well published in your field of study, multiple other postdocs all working in a synergistic way and all the while accepting you live on a ’maybe’ with regards to your future and getting paid poorly for it.” The perception of most disgruntled postdocs is this: the chances of securing a tenure-track faculty position are slim, even with tremendous passion and sacrifice, largely attributed to conditions that cannot be controlled. Many feel their hard work does not in fact pay off. The alternative perspective, and advice that we summarized from non-disgruntled postdocs: “I understand the chances of obtaining a faculty position and the challenges that come with it. However, I have a passion for this path, and I want to try to achieve it anyway, with the understanding that I will explore alternative career paths if this one does not prove successful.” We find this latter frame of mind, coupled with a framework where academic careers are one of many (not better or worse) successful career options for postdoctoral scholars, key for researchers in training.

While we did not ask the postdoc mentors about their trainee attitudes, a recent publication by seven institutions that hold Broadening Experiences in Scientific Training (BEST) programs report the results of faculty surveys of their BEST mentors to understand faculty perceptions around career development for their trainees [ 43 ]. The faculty believed that there was a shortage of tenure-track positions and felt a sense of urgency in introducing broad career activities for their trainees [ 43 ]. However, many do not feel they have the knowledge and resources necessary to guide and support the 85% of trainees who need professional development for careers outside of academia [ 22 , 41 ]. The study also found that faculty perceived trainees themselves as lacking in the knowledge base of skills that are of interest to non-academic employers. For budding scientists along the training continuum, the advice given by postdocs in this manuscript could help enhance the knowledge base to best prepare them for non-academic career tracks.

To better illustrate the cost-benefit ratio of pursuing an academic research career, we separated codes into either a benefits or costs category and indicated the frequency of references ( Fig 2 ). Codes that were more associated with the benefits of pursuing an academic research career included academic freedom, strong mentorship, network, and passion, whereas administrative obligations, backup plan, financial stability, and hard work were associated with the costs. While the frequency of codes associated with the costs outnumbered the benefits, 546 to 489, sacrifices (or costs) and benefits are weighed differently between postdoc respondents.

The codes are listed alphabetically in their respective columns. An end limit of “45” (a double of the average frequency value of 22.5) was set for the data bars to provide a representative visual comparison of the codes’ frequencies.

https://doi.org/10.1371/journal.pone.0250662.g002

Our study has several limitations. One is that the free-text method of gathering these data prevents engagement with the participant and clarification of intent. With this format, respondents have the ability to address a broad array of topics which promotes variety in their responses but limits our control over what the subjects choose to discuss. Focus groups with postdoctoral participants can explore in more depth the benefits and challenges perceived by postdocs. Due to the subjective nature of the survey respondents’ experiences, much of this work also reveals the postdoctoral trainees’ perceptions rather than absolute truths or facts about the scientific and career development process. Another limitation is that this sample is not random, and therefore frequency counts should be considered in this context. Given the large number of responses, the frequency by which codes appear can be helpful in understanding trends and emphasis in the sample, but not for comparing significance across codes. In addition, the sample population consists of postdoctoral scholars from top-ranked US universities and institutions, so their perspectives reflect the experience of those who train in similar environments. However, it is important to note that postdoctoral appointees at the top 100 institutions in the country (n = 56,092) account for approximately 88% of the total number of postdocs in the United States (n = 63,861) [ 38 ]. Therefore, our sample is representative of a significant portion of the U.S. postdoc population.

Overall, our study shows that most postdocs understand the travails and risks associated with pursuing a tenure-track faculty position in academia. Many perceive the challenges as surmountable and the reward of an academic research career worthwhile. As noted by one postdoc, “Being a successful academic researcher is somewhat akin to pursuing a career in music performance or professional sports. Science and research must be your real passion for which you are willing to work extremely hard and sacrifice. And even with hard work and sacrifice, and of course the requisite level of talent, you may not make it to the big leagues. Be sure you are willing to take this risk and that you can enjoy the journey no matter what happens.” These accounts should benefit students and trainees interested in pursuing a research career in academia by helping them make more informed decisions about their career path, ultimately enhancing the scientific workforce.

Supporting information

S1 file. responses of 994 postdoctoral researchers to a single, open-ended survey question: “what advice would you give to someone thinking about an academic research career”..

https://doi.org/10.1371/journal.pone.0250662.s001

S1 Table. Full list of codes derived from the survey responses.

https://doi.org/10.1371/journal.pone.0250662.s002

S2 Table. Original codes divided into 6 categories under the major theme, Life in Academia.

https://doi.org/10.1371/journal.pone.0250662.s003

S3 Table. Original codes divided into 14 categories under the major theme, Strategies for Success.

https://doi.org/10.1371/journal.pone.0250662.s004

Acknowledgments

The authors wish to thank Dr. Mary E. Charlson, Dr. Avelino Amado and Dr. Leslie Krushel for helpful comments.

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What Is the Tenure Track?

Tenure grants a professor permanent employment at their university and protects them from being fired without cause. The concept is closely tied to academic freedom, as the security of tenure allows professors to research and teach any topic—even controversial ones.

Tenure Track

The tenure track is a professor’s pathway to promotion and academic job security. It’s the process by which an assistant professor becomes and an associate professor and then a professor. The tenure track exists in most American and Canada universities, however, not all teaching and research positions at these institutions are on tenure track. An assistant professorship is the entry-level tenure-track position; lecturers and adjuncts are not on the tenure-track.

The Tenure Review Process

A professor who is on the tenure track is expected to go up for a tenure review 6 years after starting the position. The tenure review evaluates a professor’s contributions in three areas: research, teaching, and service to the university. Before the review process starts, the professor has to put together a tenure dossier. The dossier typically includes a CV, list of publications, comprehensive teaching portfolio, tenure statement, list of awards and grants, and details of university service. The departmental tenure committee will also solicit five to ten external letters of review from prominent senior scholars in the field. The external reviewers will evaluate the professor’s work and impact on the field to make a recommendation about whether they should be awarded tenure.

Once the external letters of review have been received, the departmental tenure committee will review the dossier and the department head make a recommendation on the tenure application. Next, the tenure dossier will go to the dean of the faculty, then the campus committee, and ultimately the provost who will make the tenure decision. If the professor is awarded tenure, they are also usually promoted to associate professor. Five to seven years after receiving tenure, an associate professor will go up for another review after which they are promoted to full professor.

Tenure in Europe

For many years, the concept of tenure as it pertains to job security, academic freedom, and career progression was a hallmark of American and Canadian universities, while professors in many European countries earned permanent positions as a result of their civil servant status. In the last two decades, many European countries have started creating tenure-track systems that more closely mimic the North American version to attract international talent and improve job security. Tenure-track positions, meaning fixed-term contracts that offer the possibility of permanent employment at a higher level after evaluation, now exist in Sweden , Italy , Denmark , Germany , Finland , the Netherlands , Switzerland , and Belgium. The tenure tracks in these countries have been set up in one of two ways. Either a completely new tenure-track assistant professor position has been created (such as in Sweden and Finland) or a tenure-track option has been added to the current position at the assistant professor level (such as in Italy or the Netherlands). As a result, many countries have a mix of old and new systems.

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The Transition from Grad Student to Assistant Professor

Introduction, types of positions, tenure review, the job: teaching, the job: research, the job: service, getting to know your department, being a professional.

Finally, the opportunity to teach your own syllabus and not have to worry about how to diplomatically deal with your student’s complaints that the lectures and readings are boring, out of date, and lack the intellectual frisson that you can bring to your chosen field of study. What does it mean to make the move from GSI and research assistant to assistant professor? No single summary can provide an adequate description of the variance to be found among different departments and the many different types of colleges and universities.

The paragraphs below are designed to give you a broad sense of what is expected of you as a tenure-track, junior faculty member. For more about the specifics of your field, talk to the faculty in your department and ask for the names of some recent PhDs from your department’s placement advisor. If there is a bias in what follows, it is towards smaller colleges and universities because in the smaller departments found in such institutions you are less likely to find peers who can advise you, and expectations based on your experience at Berkeley are likely to be less helpful as a guide.

With rare exceptions, there are two types of junior faculty positions: visiting/adjunct faculty and tenure-track. The difference between them is merely night and day. The other key distinction is between institutions that emphasize research and those which stress teaching. Here, the differences can be more subtle, and are often very difficult to gauge.

Visiting/Adjunct Professor – These positions are either part-time and/or limited, fixed term appointments. Visiting positions range from one semester to three years, and at times are renewable. Typically, visiting professors are hired to replace faculty on leave or to provide coverage in an area where the administration doesn’t want to commit a tenure slot. Visiting/adjunct faculty generally carry higher teaching loads at a significantly lower salary than their tenure-track brethren. Often they must share an office, sometimes located in the basement or some other out of the way place, and lack access to computers and other resources. You are also less likely to have control over which courses you teach and how you teach them. Given the heavy teaching demands, and especially if you have a lengthy commute, you may find it difficult to get much scholarly work done. Visiting positions can provide you with teaching experience and help keep body and soul together, but they are rarely an avenue into a tenure-track position. When such positions come open, they almost always entail a national search. Your status as the incumbent may help, but is not likely to be a decisive factor.

Lecturer – Lectureships are typically longer term than visiting/adjunct positions, but are non-tenured positions. Contracts can range up to five years, often renewable, but as above with a higher teaching load and less infrastructural support than a tenure-track position. These positions are generally found in areas such as foreign language instruction or the arts which may or may not require a PhD.

Tenure-Track (aka The Promised Land) – These are positions for which there is every expectation, and administrative budgetary commitment, that the person will receive a tenure review within seven years that if passed successfully provides for lifetime employment with the college or university. Most newly-minted PhDs are hired as assistant professors, promoted to associate upon achieving tenure, and go through an additional review, five to seven years later, for promotion to full professor. The rank of associate professor does not necessarily imply tenured status. An experienced, assistant professor who moves to another university or a PhD with significant, relevant, non-academic experience may be hired as a non-tenured associate professor generally with tenure review to follow within a year or two. An instructor is generally an ABD (All But Dissertation) hired for an assistant professor slot and is usually listed as such as soon as the degree is awarded.

Once you are hired, the tenure clock begins to tick, and usually you will come up for tenure in your sixth year. Typically, you will receive an initial two to four year contract, and go through a review in your second or third year. At some schools, these reviews are perfunctory, but at others they are a major production requiring you to assemble a substantial file including outside letters of support for your scholarship at least some of which are from people who were not on your committee or in your placement file. If you are successful in this first review, you receive an additional contract that will take you through the probationary period. If not, you usually have a remaining academic year on your contract to find a new position. At most research-oriented colleges and universities, you will receive a semester or year-long paid sabbatical after successfully navigating this review.

The tenure review generally occurs in your sixth year, though at most institutions you can choose to come up for tenure earlier. If you are hired as an ABD, are injured or disabled for a significant period of time, get grants to take an unpaid leave, or have a child during your probationary period you may be able to negotiate having your clock stopped for a semester or a year. If you are offered a tenure-track job as an ABD, the time to raise the possibility of an extension is when you are hired (and they are still dazzled by you) and not two years later.

The review process is one of the most demanding and nerve-wracking experiences you will ever have to go through – with good reason. You are asking your department and institution to allocate a significant share of their resources to you for the next thirty to forty years. On the other hand, if you receive it you gain a measure of security and freedom in your chosen profession that is extremely rare in contemporary society. You need to start thinking about what you want to have in your tenure file from the minute you accept their offer.

The tenure file begins with

• Evidence of your teaching record and evaluations,
• Copies of all your publications and/or artistic creations,
• Outside letters assessing your scholarship and standing in the field, and
• A record of your service to the institution and administrative contributions.

The file is usually completed by October and made available to all the tenured members of the department. Letters are then written by every tenured member of the department (if it is small) or tenured members of your sub-field and interested others (if it is large) which then become part of the file. There is a formal vote by the department, and the resulting recommendation is communicated in the form of a final letter from the chair, representing the overall view of the department. The file is now complete.

At most but not all schools, the recommendation of the department is then forwarded along with your dossier to a committee of tenured faculty drawn from a range of departments which may or may not endorse the recommendation of the department. Depending on the size of the institution, your file may pass up through more than one such committee. Finally, it is up to the president, provost, or chancellor to make the final decision. Presidents et. al. usually have absolute discretion in this regard, and may choose to reject unanimous recommendations from below.

Throughout the following paragraphs, there are references to choices that should be made by junior faculty (the non-tenured) with at least some consideration of how it will impact your ability to present as impressive a tenure file as possible. This is not meant to convey cynicism, but it’s important to realize that absent tenure you will be unable to accomplish most if not all of the goals you set for yourself when you decided to enter academia. You will need to ask yourself whether a given project, course, or commitment should be started now, or deferred until after you’ve satisfied the powers that be that you deserve the commitment that tenure entails.

As an assistant professor your job consists of three components: teaching, research, and service to the institution (serving on academic and administrative committees). The relative importance of these three varies widely depending on the institution and its requirements for tenure.

At a major research university or top-ranked small college, the teaching load is typically 2-2 (two courses per semester, and at a university you may teach graduate and undergraduate versions of the same course each semester) in the social sciences and humanities – less in the sciences and engineering. At the other end of the spectrum, there are many colleges and some universities where faculty carry a 4-4 teaching load. Even in the latter case, it is unlikely that you would be asked to teach eight different courses, and a distinction is commonly made between the number of courses you teach and the number of preparations (i.e., teaching the same syllabus more than once in a semester or year). The number of preparations you are required to teach may be almost as important as the number of courses, and this is often negotiable for first year faculty if you remember to ask.

Creating new courses can require an enormous investment of time and energy especially if you teach in a field where textbooks are rarely utilized. No one (rather no “sane” one) teaches five new courses their first year. Borrow from your friends, and remember imitation is the sincerest form of flattery.

Some institutions and departments have set curriculum and teaching methods, especially for intro and core courses, but for the most part you will enjoy wide latitude in designing and teaching your courses as you see fit. It is important, however, to think about how your style of pedagogy fits with the prevailing culture of your new home. Students at small colleges (especially the better ones) will resist having to listen to lectures on an ongoing basis without the opportunity to participate. At the same time, a purely Socratic approach is likely to bog down in an intro class of 500. You want to find a style and approach that fits your personality and your pedagogical philosophy, but it also makes sense to recognize that you are not teaching in a vacuum. If you encounter difficulty, as most do, talk to your new colleagues. Everyone has gone through the same adjustment, and most are happy to help.

In addition to coursework, the teaching function typically involves advising incoming first year students, majors, and supervising independent studies and senior theses. First year faculty are usually exempt from these duties. They can be among the most satisfying parts of the job, but they can also be very time consuming. In a similar vein, you may be asked to teach as a part of a multi-disciplinary team (e.g., The Renaissance, or The Emergence of the Pacific Rim). This can be a fun and stimulating experience and a good way to get to know faculty from other departments. But team-taught courses tend to be more work, and you are very unlikely to get much credit for being a good corporate citizen when the tenure committee meets.

Higher education is getting increasingly competitive, and there are very few colleges and universities that are not keenly interested in their relative status and prestige as reflected in guidebooks and, especially, US News and World Reports. One of the keys to increasing an institution’s visibility and ability to attract good students, in the minds of most senior officials, is the reputation of its faculty as reflected by publications and other markers of recognition and achievement (e.g., getting grants). You may find yourself at a place where many tenured and senior faculty haven’t published for years, if ever, but times have changed. Many schools which used to look only at teaching, service, and general amiability, now expect publications in a tenure file.

Across the spectrum of institutions, expectations have ratcheted upwards. Where a few articles would have sufficed a few years ago, you now need a book. Instead of a book, you need a book (at a university or prestigious commercial press) and clear evidence of progress on a post-dissertation project.

You are unlikely to ever get a clear answer to the question how much am I expected to publish for tenure. The best you can do is try to assess what recently successful candidates have done in similar fields. You need to be aware that different disciplines, even if closely related, may have different standards. Political scientists for example write books, economists write monographs and articles. If your primary medium of scholarly expression is relatively new (computer software, multimedia, internet-based journal) or unusual (e.g., plays directed, dances choreographed, exhibitions curated) you need to educate those who will evaluate your scholarly production sooner rather than later. Don’t assume that they must have done it before, especially at a smaller institution.

Don’t delay sending out draft articles and manuscripts until you have it just right. You will likely have to revise it on the basis of reviewers’ comments anyway. Let it go. Time is of the essence, and passes shockingly fast, even if you don’t have small children. There are few places in life where the perfect is more of an enemy of the good/publishable.

After your first year, you will probably be asked to serve on one or more faculty committees. These committees are responsible for governing and supervising a wide range of activities at the institution. Here again you need to practice moderation. Many committees tackle important issues that will have a substantial impact on an aspect of the institution that interests you deeply, but will also be very time consuming.

Other forms of service include organizing a conference or lecture series, serving as advisor to a student organization, taking on a part-time administrative position (e.g., assistant director of Asian Studies).

Beware, it is important to interact with colleagues from other departments , (some of whom will sit on the committee that will review your tenure file) on a professional basis and many service activities are both interesting and important. On the other hand, it is a rare institution where great service can overcome mediocre research and teaching. You need to find a balance; you need to be careful.

Your department is where you live, your family. Like many today, it may be an extremely dysfunctional one, but it’s yours. The first hurdle you must overcome on the road to tenure is to obtain the strong endorsement of your department. You may not like some of them, but you need to gain their respect.

Your first challenge is to learn the lay of the land. The first few departmental meetings will be very disorienting as names and phrases fly across the table as a series of allusions, metaphors, and shorthand evoking laughter or derision while you sit there dumbfounded. It will take some time to learn the informal patterns and organizational culture that characterize your new home, but it is important to make the effort. Many of the opinions and positions held by individuals and factions and the bases of their unwillingness to “try that again” (no matter how compelling your logic), will remain inexplicable absent an understanding of the departmental and institutional history.

It is unlikely that you have ever been exposed to politics as pervasive and at times as vicious as you will find in many institutions of higher learning. People live together for many years, and insults real and imagined can fester for a long time. Your job is not to be consumed by it, but to learn enough not to be caught in the middle.

Most of what you need to know will not be expressed at formal meetings. If your department has informal get togethers, attend them. Ask innocuous-sounding questions about names you’ve heard or issues you don’t understand, and allow them to tell stories. If the members of your department aren’t collectively very social, suggest some ways of getting together as a group or individually. Even if you’re not terribly athletic, going to the gym or playing racquetball is an excellent way of relieving stress and getting to know your colleagues in a less guarded setting.

As a professor you need to engender the respect of your fellow faculty members and create an appropriate social distance between yourself and your students. A senior colleague once described his first semester at the college where he had dressed very informally and treated the students as peers only to have one of them express dismay and disappointment at the low grade he had received from his buddy the professor.

Women and those whose hair has not yet begun to gray may have a more difficult time engendering the respect they deserve. It may seem odd at first, but let students call you “Dr.” or “professor” (even if you’re still ABD), even if you’d rather go by your first name. If your colleagues neglect to use your title (especially in front of students, parents, colleagues, or administrators) and refer to you as “Mr.” or “Ms.,” gently but firmly correct them in private. They probably don’t mean anything by it, but you have enough to worry about without the added confusion about your professional status.

You need not carry the burden of appearing omnipotent and all knowing. It is perfectly acceptable to respond to a question with “I don’t know. It’s an interesting question. I’ll look it up before next class.” One of the greatest benefits of a Berkeley PhD is that for the rest of your life, you can say “I don’t know,” and not feel stupid because you have a piece of paper from one of the world’s leading universities attesting to that fact.

At the same time, don’t overestimate your relative ignorance in areas outside of your specific research specialty. An undergrad is not going to challenge your interpretation of the origins of the Dead Sea Scrolls by citing the new article in American Scholar that you haven’t yet gotten around to reading. Relax, if you say it, they’ll believe it.

At least for a while, in your heart of hearts you’ll be confident only that the university will soon enough discover its error in awarding you the PhD, and at some point will brand you (in public no doubt) the fraud you know you are. This too will pass as you come to realize that students are extremely gullible and many of your colleagues are even greater frauds than you. That is to say, you know more than you think you do, and students and the people you work with will appreciate the range and depth of your knowledge and abilities if you let them.

If you feel students and colleagues are not according you the respect you deserve, talk to more senior colleagues or other junior faculty who have likely shared the same experience. It’s much easier to ease up once you have established yourself as a professional, than the reverse.

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• v.7(35); 2021 Aug

Myths and facts about getting an academic faculty position in neuroscience

Prior funding and/or papers in high-profile journals are not necessary to obtain a tenure-track faculty position.

We at the National Institute of Neurological Disorders and Stroke routinely receive questions and statements from trainees and faculty that suggest widespread beliefs about the necessity of a National Institutes of Health K99/R00 award, other prior funding, and/or specific types of publications for obtaining one’s first tenure-track position in neuroscience. To address these beliefs, we examined the funding and publication history of a cohort of investigators who began their first academic faculty position between 2009 and 2019, and we interviewed several senior academic leaders with extensive experience in hiring new faculty. Our data show that <11% of newly hired faculty had a K99/R00 award and that neither prior funding nor papers in prestigious journals were necessary to obtain a tenure-track faculty position. Interviews with academic leaders almost uniformly referred to critically important factors that were considered to be more important in the hiring process than funding or publishing in high-profile journals.

INTRODUCTION

At the National Institute of Neurological Disorders and Stroke (NINDS), we hear many rumors and myths about funding from the extramural community. One of the most pervasive myths relates to the role of funding in obtaining a tenure-track or equivalent academic faculty position. Clearly, in many faculty positions, scientists must obtain funding to be considered successful researchers, and oftentimes, to obtain tenure. The number of opportunities for trainees to write grants and obtain funding, combined with the success of many individuals who obtain funding as a postdoctoral fellow, has led to the widespread belief that obtaining research funding while in a postdoctoral position, and even while in a predoctoral position, is critical to career success. Similarly, myths abound regarding the importance of certain kinds of publications, numbers of publications, and the requirements for moving from temporary, junior faculty positions to a tenure-track faculty position. It must be noted that belief in these myths is not confined to trainees; we hear from many established faculty members about the need for their trainees to have a grant or a certain kind of paper to be competitive for an academic faculty position. These beliefs place a great deal of stress on postdocs and students and often drive trainees to pursue research projects that are not to their advantage. For example, the belief that one needs to have a publication in a Cell , Science , or Nature (CSN) journal can lead to the pursuit of very large, complex, and/or difficult projects and could prolong time in training because of a primary goal of obtaining a publication in one of these “high-profile” journals. These beliefs lack solid evidence to support them. For example, an observation that many postdoctoral fellows who have individual funding or publications in high-profile journals obtain faculty positions does not translate into these metrics of accomplishment being necessary for success. The pursuit of unnecessary accomplishments, which often require an extensive focus on data collection, could result in trainees missing opportunities to develop critical skills and gain broader and deeper knowledge that could have major long-term benefits to their careers and their ability to innovate in their field.

As junior scientists prepare for the academic job market, they often face anxiety and uncertainty about their readiness to compete for a tenure-track faculty position. There is a dearth of publicized, factual information on what institutions value in academic faculty job candidates. Many believe that there is a narrow, archetypical set of qualifications that are required to obtain one of these coveted positions. In this study, we have obtained data to address the veracity of these myths. In part I of this paper, we present data using an “early-stage investigator” [ESI; without a National Institutes of Health (NIH) R01 and <10 years from obtaining their doctorate] cohort, composed of individuals who successfully obtained tenure-track faculty positions over a 10-year period to address five specific myths about the requirements for success. Then, in part II, we present qualitative information obtained from interviews with six individuals who have extensive experience in hiring new faculty members to find out what they and their search committees look for when hiring individuals into their first, tenure-track, assistant professor positions. These individuals represent six well-funded, research intensive institutions of different sizes and characteristics, and together, these interviews provide a compelling description of what a broad array of hirers are looking for.

Part I of this paper describes data that addresses the following five myths:

1) One needs a K99/R00 to obtain an academic faculty position. This myth is perhaps the most common we hear and the cause of enormous stress among the postdoctoral community. We constantly hear from postdocs how critical it is for their career to obtain a K99/R00 and expressions of the disastrous results that await them if they do not get one.

2) One needs to have research funding to be competitive for an academic faculty position. When we have presented data to an individual showing that it is not necessary to have a K99/R00 to obtain a faculty position, a common response is, “Well, you need funding of some sort.”

3) One needs an NIH F32 to be competitive for an academic faculty position. The F32 is a long-standing, widespread NIH-sponsored fellowship for postdoctoral fellows. NIH success rates for obtaining F32 support have ranged from 25 to 30% over the past 10 years, and it is believed by many to be a critical stepping-stone to obtaining an academic faculty position.

4) One needs to publish a CSN paper to obtain an academic faculty position. This is commonly heard among both established faculty and trainees as a reason for trainees to pursue very complex problems and often as a justification for prolonging predoctoral or postdoctoral training.

5) If one takes an “intermediate” position (a position between postdoctoral fellowship and tenure-track faculty), then subsequent transition to a tenure-track faculty position requires funding or publication of a CSN paper during that intermediate position. Historically, it was unusual for individuals to obtain a tenure-track position subsequent to taking a junior faculty position with titles such as “research assistant professor.” However, over the past decade, intermediate positions between postdoctoral fellow and tenure-track assistant professor have proliferated (see Materials and Methods for academic titles we defined as intermediate positions). So we asked two questions: (i) Are there many individuals hired into tenure-track positions from intermediate positions and (ii) for those who transition from a postdoctoral fellowship position to an intermediate position, must they have a “big accomplishment” in the intermediate position, such as obtaining competitive funding or publishing in a CSN journal, to transition to the tenure-track position?

Part I: Data that address the five myths

The approach and cohort.

There is no database that we know of that lists all of the individuals hired into neuroscience-focused tenure-track or equivalent positions. Therefore, we examined a defined cohort of research scientists hired into assistant professor positions during the “K99 era” (between 2009 and the present) and asked, “what were their accomplishments prior to being hired?”

The cohort for this study included 344 individuals who occupied assistant professor or equivalent academic faculty positions. The cohort was defined by the following requirements: First, we identified all individuals who applied as principal investigator (PI) for an NINDS R01 and were designated as an ESI, between fiscal years 2015 and 2017 (inclusive; thus, three fiscal years or nine R01 due dates). There were 592 unique ESIs who applied for an NINDS R01 at one of these nine due dates. Because clinician-scientists are subject to very different hiring considerations than individuals with PhD degrees only, we confined the cohort to those with a research doctorate (e.g., PhD) who did not have a clinical degree (i.e., we eliminated all individuals from the cohort who had, for example, an MD or a PhD in a field that includes a license to practice clinically). Last, because this study originated to address the myth regarding the need for a K99/R00 to obtain a faculty position, we limited the cohort to those individuals who were hired between 1 January 2009 and the present (the K99 was initiated in late 2007, with the first transitions to an R00 at NINDS occurring after 1 January 2009).

Characteristics of the cohort

The 344 members of this cohort were hired into their tenure-track positions at 133 different institutions, with 22 of these 133 institutions hiring five or more of these individuals. The mean time to completion of their PhD training was 5.0 ± 1.0 years (SD; median = 4.8 years), with 91% of the cohort completing the PhD training within 6 years. All members of the cohort transitioned into postdoctoral positions. The mean and median duration of postdoctoral training were 4.5 ± 1.7 (SD) and 4.6 years, respectively, with 79% of the cohort completing postdoctoral training within 6 years and 93% finishing their postdoctoral training in 7 years or less. The average time from completion of the PhD to start of tenure-track position for the entire cohort was 5.9 ± 2.1 years (SD; median = 6.1 years), with 73% obtaining their position within 7 years of degree and 98% within 10 years of degree. Before beginning their faculty positions, members of the cohort published, on average, 13 ± 8 papers (SD) and were listed as first author on 6 ± 3 (SD) of those papers.

Important note: Our cohort consists of individuals who successfully began a tenure-track, academic faculty position. We did not obtain information on a comparison cohort of individuals who did not begin a tenure-track position. Thus, we have not addressed, and are not describing in this paper, what makes the difference between success and failure in obtaining an academic position. The data below specifically address the myths described above, in the form of the question, “do you need [something] to obtain a tenure-track or equivalent position?”

Myth 1: One needs a K99/R00 to obtain an academic faculty position

Perhaps the number one myth that we hear at NINDS is that you need a K99/R00 to get an academic faculty position. We hear this not only from postdocs but also from experienced faculty and even occasionally from NIH staff. To address this myth, we determined how many individuals in our cohort were successfully awarded NIH K99/R00 grants. Of the 344 individuals in the cohort, only 14% (48 of 344) had a K99 award ( Fig. 1 ).

To the left of the dashed line, individuals are listed in only one category. The binning priority for the few individuals who obtained multiple awards was K99 funding, R01 funding, non-NIH funding, K01/K25 funding, and R03 or R21 funding. The bar to the right of the dashed line indicates the number that obtained multiple competitive grants before obtaining their tenure-track faculty position. Fellowship funding, including the F32, was excluded from this analysis.

We have subsequently completed the same analysis for an identically defined cohort from the years 2018 to 2019 (i.e., the two fiscal years subsequent to those from which the main cohort was drawn). There were 258 unique individuals in this cohort. Of these 258 individuals, 35 (13.5%) had a K99. Together, over the 5-year period from 2015 to 2019, 14% of the 602 individuals who were hired into assistant professor positions since 2009 and applied for an NIH R01 as an ESI had a K99 award.

These analyses put an upper limit on the number of individuals being hired who had a K99/R00 award at 14%. However, this is an overestimate. Our cohort does not include the many individuals hired into tenure-track positions who do not apply for R01 funding within the first few years of starting their faculty position. For example, over the 5-year period from 2015 to 2019, there were 351 unique individuals designated as “new investigator” (NI; defined as somebody who never obtained an NIH R01 and is >10 years from obtaining their doctorate) who met all other criteria of our cohort with no overlap of individuals. Only 19 (5%) of these NIs had a K99/R00 award. If we then combine both ESI and NI populations, then only 11% of these 953 (602 plus 351) individuals had a K99 award before obtaining their faculty position.

Even this figure of 11% must be an overestimate of the number of K99 awardees among those hired. Most K99 awardees apply for an R01 during or shortly after completion of their R00 award (96% of individuals with an NINDS R00 have applied for an R01 by the end of the R00 period; such individuals populate the numerator) and will thus be accounted for. However, there will be a large number of individuals hired into tenure-track faculty positions that have not applied for an NINDS R01 early in their faculty careers (e.g., those who applied for other NIH grant mechanisms, such as an R21 or R15, or those who receive funding from other agencies, such as the National Science Foundation, or from private foundations). For example, we identified all of the individuals who applied for an NIH R15 between 2015 and 2019 and were hired in the K99 era. None (more than 200 individuals) had a K99/R00 award. These individuals would add to the denominator (total number hired into faculty positions) and thus make the percentage of those hired who had a K99 even smaller. Similarly, there are the many individuals hired into tenure-track positions that have not applied to NIH for funding. It is highly likely that very few or none of these would have had a K99 award; all of these individuals would add to the denominator and further reduce the percentage of K99 awardees among those hired into tenure-track positions.

Myth 2: One needs to have research funding to be competitive for an academic faculty position

In our experience, this myth is the broader issue for those who believe you must have a K99 to obtain a tenure-track faculty position. The K99/R00 has a lot of visibility with respect to its value in helping postdocs obtain faculty positions, but there are many other opportunities for postdocs to obtain funding, both from private foundations and from NIH. We hear repeatedly not only from postdocs (and often their mentors) but also even from students that trainees must obtain competitive funding to obtain a faculty position.

To examine this myth, we determined how many individuals in our cohort had research funding as PI before obtaining their tenure-track position. We envisioned this myth as being related to an individual having an active grant to take to the position. However, for this analysis, we did not consider whether the grant was active at the transition point of taking the position. We simply determined whether the individual had obtained funding at any time before obtaining the faculty position.

In addition to the 14% of our cohort who obtained a K99/R00 award, another 3% of the cohort obtained non-K99, K-series funding, 8% obtained R-series funding, and 15% obtained non-NIH funding before the start of their faculty position ( Fig. 1 , left of dashed line). Thus, 40% of the cohort obtained competitive funding before being hired. Twenty-three individuals obtained two grants before their tenure-track position ( Fig. 1 , right of dashed line). Most critical to addressing the myth, however, is that 60% of individuals in this cohort who obtained a tenure-track faculty position had no funding before obtaining that position.

To examine this another way, we asked how many of the institutions represented in this study hired an individual into their tenure-track position when that individual had not received competitive funding. Eighty-two percent (109 of 133) of the institutions represented in this study hired individuals into tenure-track positions who had not obtained competitive funding before being hired.

Myth 3: One needs an NIH F32 to be competitive for an academic faculty position

Another myth that we encounter from trainees and many mentors is that an F32 is a necessary stepping-stone for a successful career in academic research. Applying for, and even getting, an F32 has many scientific and training benefits. However, the data ( Fig. 2 ) indicate that the vast majority of those hired into a tenure-track position did not have an F32 as a postdoc. Only 17% (58 of 344) of our cohort that held tenure-track positions were supported by an F32 during their postdoctoral research period ( Fig. 2 ). Twenty of these fifty-eight individuals secured more substantial individual funding (e.g., K99/R00 or R-series grants) before their faculty appointments. Consequently, only 11% (38 of 344) of our cohort were awarded an F32 and no other funding before obtaining their faculty position. Perhaps more directly to the point, if one subtracts out all of the individuals from the cohort who had funding other than an F32 (to determine the prevalence of F32 funding among the 60% of the tenure-track faculty who were hired without a K99/R00, R-series grant or foundation funding), then only 19% of those hired had an F32.

Although it is reasonable to assume that obtaining competitive funding would increase the competitiveness of an applicant for a faculty position, the data above clearly demonstrate that it is not needed for success. Our information derived from interviews with individuals who hire faculty (part II below) was remarkably consistent with this conclusion. As described below, two of six institutions we talked to considered funding to be essentially irrelevant to their hiring decisions, and only one institution used funding as a screening tool.

Myth 4: One needs to publish a CSN paper to obtain an academic faculty position

The CSN family of journals (i.e., includes Nature Neuroscience , Neuron , etc.; collectively termed CSN below) are often held as the gold standard of scientific journals. Consequently, many trainees, often encouraged by their supervising faculty, strive to publish in these journals and often believe that their success hinges on publications in these journals.

To address this myth, we examined the cohort’s publication record before beginning their tenure-track position. We identified all peer-reviewed research articles (i.e., we did not include reviews, book chapters, abstracts, etc.) published in each career stage (predoc, postdoc, and intermediate position) by members of the cohort and whether the individual appeared as first (including co-first) author or middle author.

Figure 3 illustrates how many first-author CSN papers were published by the individuals in the cohort. Fifty-nine percent of those hired into tenure-track positions did not have a first-author publication in a CSN journal before obtaining their position. In addition to the 41% of the cohort that had published a first-author paper in a CSN journal, an additional 11% held a middle author position on a CSN journal article. Thus, approximately half of the population in this cohort did not have a CSN paper on their curriculum vitae (CV).

Myth 5: If one takes an intermediate position (a position between postdoctoral fellowship and tenure-track faculty), then subsequent transition to a tenure-track faculty position requires funding or publication of a CSN paper during that intermediate position

Historically, the vast majority of individuals in tenure-track or equivalent positions transitioned directly from postdoctoral positions. It was rare for an individual to transition to a non–tenure-track faculty position, such as one that might have a title of research assistant professor, and subsequently transition to a tenure-track position. In recent years, however, the number and kind of positions intermediate between postdoctoral fellow and tenure-track faculty has proliferated and the number of individuals taking them has similarly grown.

It was instructive to us how common and complex the transition to an intermediate position had become. The nature of these positions varies not only by title but also even within title across institutions. For example, a research assistant professor in one institution might have independent space and be expected to bring in major research funding, whereas an individual in an identically titled position in another institution might be working in a senior faculty member’s laboratory and conducting research funded by that faculty member’s grant. The most common titles were “instructor,” research assistant professor, and “research associate,” which in some institutions were positions to which postdocs were promoted after a period of time (while maintaining the essential component of being in a mentored training position) but in other institutions appeared to be a junior faculty position. These positions carried privileges such as the ability to apply for an NIH R01 and, importantly, provided fringe benefits not available to postdoctoral fellows. However, in the former cases, individuals were not independent and were still functioning as advanced postdoctoral fellows (i.e., working in a mentor’s space, working on a mentor’s project, and funded by the mentor), whereas in the latter they were functionally independent. In our analysis, we considered all “intermediate positions” identically; when parsed out into different position titles, the results we will present below were qualitatively identical.

The different pathways to a tenure-track position represented in our cohort

Upon completion of a period of postdoctoral training, roughly half of our cohort transitioned directly into a tenure-track position and roughly half transitioned into an intermediate position before obtaining a tenure-track faculty position ( Fig. 4A ). As expected, the time between obtaining one’s doctorate and starting in a tenure-track position was quite different for the two groups, with those spending time in an intermediate position taking approximately 2 years longer post-degree to obtain their tenure-track position ( Fig. 4B ).

( A ) The number of individuals who transitioned directly from postdoc to faculty (blue) or transitioned from postdoc to an intermediate position before obtaining a faculty position (orange). ( B ) The average time from degree to tenure-track faculty position for the two career trajectories. The median and range in (B) were as follows: blue (median: 5.2 years; range = 0.5 to 9.8 years) and orange (median: 6.8 years; range = 2.7 to 17.0 years).

Transitions directly from postdoc to tenure-track faculty position

Figure 5 presents histograms of the number of first-author predoctoral and postdoctoral research articles for individuals who transitioned directly from postdoctoral to tenure-track faculty positions. The mean and median number of pre- and postdoctoral first-author papers for this group was 3 and 2, respectively. Twenty-three individuals did not have a first-author postdoctoral publication before starting their faculty position and approximately half had either 0 or 1. Figure 5C illustrates the total number of first-author papers for those who transitioned straight from postdoctoral to faculty position. Whereas the mean and median number of publications were both approximately 5 before obtaining their tenure-track position, 24% had three or fewer first-author publications when they were hired onto the faculty. Although we have not attempted to evaluate papers for significance or quality, these data indicate that one can obtain a faculty position with a small number of first-author publications.

( A ) During graduate school, ( B ) during the post-doctoral period, and ( C ) in total ( n = 162). Only peer-reviewed research articles are included; reviews, book chapters, and other types of publications are not included.

Figure 6 illustrates the funding and CSN publication status of the group of individuals who transitioned directly from a postdoctoral position into a tenure-track position. Only 15% of the individuals in this group had an NIH career development (K-series) award before obtaining their faculty position. Another 11% had competitive funding from a non-NIH source (e.g., foundation). Of the 120 individuals (74% of the group) who did not have funding, 50 (31% of the group) had a first-author CSN paper. Thirty-three individuals in this group had both funding and a first-author CSN paper before obtaining their faculty position, with 23 individuals having NIH funding and 10 individuals having non-NIH funding. Together, 57% of the individuals who transitioned directly from their postdoctoral fellow position to a tenure-track position had either some sort of competitive funding or a first-author CSN paper. Critically, 43% transitioned to a tenure-track position without having obtained research funding or a first-author CSN paper.

On the left side of the dashed line, individuals are listed in only one category and were binned first based on funding and second based on CSN publication status. The bar on the right side of the dashed line indicates the number of individuals who had both funding and a first-author CSN publication before obtaining their tenure-track faculty position.

Transitions to an intermediate position before obtaining a tenure-track faculty position

For those who took an intermediate position before moving into a tenure-track position, the outcome was similar. Figure 7 shows histograms that illustrate the number of first-author papers from their predoctoral work ( Fig. 7A ), postdoctoral fellowship period ( Fig. 7B ), intermediate period ( Fig. 7C ), and total before obtaining tenure-track position ( Fig. 7D ). The total publication record of this group was only marginally different (~1 more first-author paper) than that of the individuals who transitioned straight from a postdoc to faculty position. Moreover, 33% of these individuals published no additional first-author papers from the intermediate position before obtaining a tenure-track position and approximately half of these individuals added either 0 or 1 first-author papers during this period. Thus, adding any publication during this period, not to mention a high-profile publication, was not a requirement for obtaining a tenure-track position.

( A ) during graduate school, ( B ) during the post-doctoral period, ( C ) during the intermediate position, and ( D ) in total ( n = 182). Only peer-reviewed research articles are included; reviews, book chapters, and other types of publications are not included.

Figure 8 illustrates the funding and CSN publication status of the group of individuals who transitioned from an intermediate position to a tenure-track faculty position. Fifty-three percent of this group had competitive funding of some sort before obtaining their faculty position, and thus, critical to addressing the myth, approximately half of this group obtained a tenure-track position having obtained no competitive funding. Of the 85 individuals who did not have funding, 34 had a first-author CSN paper. Of the 25 individuals that had both funding and a first-author CSN paper before obtaining their faculty position (right side of Fig. 8 ), 18 had NIH funding and 7 had non-NIH funding. Together, 72% of the individuals who transitioned from their intermediate position to a tenure-track position had either some sort of competitive funding or a first-author CSN paper. Twenty-eight percent of these individuals, who had been in training for over 11 years on average, had neither research funding nor a first-author CSN paper before their transition to a tenure-track position.

To the left of the dashed line, individuals are listed only in one category and were binned first based on funding and second based on CSN publication status. The bar on the right side of the dashed line indicates the number of individuals who had both funding and a first-author CSN publication before obtaining their tenure-track faculty position.

Dynamics of taking an intermediate position

As described earlier, we found that the meaning of intermediate position titles varied considerably, not only across institutions but also occasionally within institutions. As a result of this ambiguity, we treated all “intermediate” positions identically in our analysis. This was less than satisfying, as we were grouping individuals into one category who ranged from advanced postdoctoral fellows to junior faculty. However, when we removed certain groups from our analysis on the basis of a particular intermediate position title, the results were qualitatively identical.

Taking an intermediate position outside of the postdoctoral institution

Figure 9A summarizes the various paths taken by those who transitioned to an intermediate position. Only 27 individuals (8%) in the entire cohort obtained a tenure-track or equivalent position after transitioning to an intermediate position outside of their postdoctoral fellowship institution. Most telling was that only 7 individuals (2% of our entire cohort) transitioned to an intermediate position at an institution outside of their postdoc institution and subsequently obtained a tenure-track position at a different institution than that of their intermediate position. Thus, inasmuch as the lack of control group prevents us from evaluating the wisdom of pursuing this pathway, our data suggest that this is a rare pathway to a tenure-track position.

( A ) The career paths of individuals who transitioned from an intermediate position to tenure-track faculty ( n = 182). The green bar at the top represents the number of individuals who obtained an intermediate position at the same institution as their postdoctoral position. The yellow bar at the top represents the number of individuals who moved to an intermediate position outside of their postdoctoral institution. The bottom bars represent those who were hired by an institution where they had been during a training career phase (gray) or an institution where they had never worked (orange). ( B ) The funding and CSN publication status before tenure-track faculty position for those who transitioned from an intermediate position to their faculty position (binned by career path).

Despite the small number of individuals, it was still of interest to know whether individuals who followed this pathway had to obtain funding or publish a CSN paper to obtain a tenure-track position. Of the 27 individuals who obtained a tenure-track position after taking an intermediate position outside of their postdoctoral institution, 15 (56%) obtained funding or published a first-author CSN paper while in their intermediate position ( Fig. 9B , top two rows combined). Thus, nearly half obtained tenure-track positions without them. Unexpectedly to us, only one of the seven individuals who transitioned to a faculty position in a new institution after a prior transition to a new institution for an intermediate position obtained one of these major accomplishments before obtaining the faculty position.

Taking an intermediate position within the postdoctoral institution

Of the 182 individuals who transitioned to an intermediate position, 85% did so within their postdoctoral institution ( Fig. 9A ). Of the 155 individuals in this group, approximately half (55%) were promoted to tenure-track positions within their postdoctoral institution and nearly half (45%) were hired at an institution different from their postdoctoral institution ( Fig. 9A ). Overall, approximately half (55%) of those in an intermediate position obtained funding or a first-author CSN paper while in the intermediate position ( Fig. 9B , rows 3 and 4 combined). Conversely, approximately half transitioned to a tenure-track position without having obtained funding or publishing a first-author CSN paper in the intermediate position. Although the numbers are small, it is of interest that obtaining funding or publishing a CSN paper appeared to be less important for being hired into a new institution ( Fig. 9B , row 3) than to be hired by the current institution ( Fig. 9B , row 4).

The apparent importance of being a “known quantity”

The data in Fig. 9 were notable in another regard. Of the 182 individuals who transitioned to an intermediate position, 105 (58%) were hired into a tenure-track position at the institution where they were currently working. When one considers both those who transitioned to an intermediate position and those who transitioned to a faculty position directly from a postdoctoral position, 41% of the 344 individuals in the entire cohort were hired into a tenure-track position at an institution in which they trained or were previously employed (i.e., where they were “known”).

We next examined how common this practice was across institutions. Table 1 lists all of the institutions that hired five or more individuals in this cohort. Eighty-two percent of these institutions hired at least one individual with whom they had previous experience, either as a trainee or employee. At 10 of the 22 institutions on this list, 50% or more of the hires were known to the institution as a previous trainee or employee. Across the entire cohort of 133 hiring institutions, 55% hired one or more individuals that were known to it by previous training or employment. Thus, it is clear that many institutions show a preference for hiring individuals that they “know.”

Summary of part I

The first four myths pertain to the belief that one needs funding or a CSN paper to be competitive for a tenure-track faculty position. We examined three categories of funding: the K99/R00 award, which, in our experience, is the award that many postdocs feel is the key to obtaining a faculty position, other types of NIH or non-NIH funding, and the F32.

Without a doubt, a K99/R00 award has many benefits both from the K99 phase of funding and the R00 phase of funding. Discussions of these benefits are beyond the scope of this paper and will be addressed elsewhere. Our data clearly demonstrate, however, that a very small percentage of individuals hired into tenure-track positions had a K99/R00. For individuals conducting research in the NINDS mission who were hired into a tenure-track academic position at an institution that has an expectation of R01 submission, our data indicate that 11% or fewer had a K99 award; and for those hired by the many institutions that do not have an expectation of R01 funding but who were running a research program as evidenced by seeking NIH funding for their research, none had a K99 award.

Equally clear from our data is that major funding of any sort is not needed to obtain a tenure-track faculty position. When one combines all sources of competitive research and non-“fellowship” career development funding, 60% of individuals hired into tenure-track faculty positions had no funding before obtaining their tenure-track position. Moreover, the willingness to hire an individual who had not received prior competitive funding was widespread. Of the 133 institutions in this study who hired an individual into a tenure-track position, 82% hired an individual who had not received prior competitive funding.

The data also clearly demonstrate that the F32 is not a critical factor in one’s ability to obtain a faculty position. A total of 464 postdoctoral neuroscientists received F32 awards from NINDS between 2007 and 2016 (individuals funded during these years would have had time to transition to faculty positions in the time relevant for this study), yet only 58 individuals in our cohort had obtained an F32. One would certainly imagine that some individuals who are hired into faculty positions would have had an F32 as a postdoc. Consequently, our data that only 11% of our faculty cohort had an F32 and no other funding, and only 17% of the cohort overall had an F32, suggest that having an F32 has a relatively unimportant role (and perhaps even no impact) in enhancing one’s ability to obtain a faculty position.

Our data also demonstrate that CSN papers are not necessary to obtain an academic faculty position; approximately half of the population in the cohort did not have a CSN paper on their CV. This leaves the possibility that one must have either funding or a CSN paper to obtain a faculty position. Within the entire cohort of the 344 individuals who obtained tenure-track or equivalent positions, 35% had neither postfellowship funding nor a first-author CSN paper. Certainly, one can look at this from two perspectives. On the one hand, 65% of those hired had obtained either a competitive grant or published a first-author CSN paper before being hired. Conversely, over one-third of the cohort had neither funding nor a CSN paper before obtaining a tenure-track faculty position. Although undoubtedly beneficial, these data argue that neither one of these two accomplishments are necessary for one to transition to a tenure-track position. Moreover, as we demonstrate below in the qualitative section of this paper, many research-intensive institutions consider other factors to be much more important than these metrics of accomplishment.

Any reasoning that is applied to these results is a bit circular. It is students and postdocs who do the experiments that generate most or all CSN papers, and there is a substantial amount of NIH and non-NIH funding that is targeted specifically to those in pretenure-track (training) career stages. Consequently, one would expect that individuals who have the training and research excellence to obtain competitive funding or publish in a CSN journal to be the same as those who have the training and research excellence to be competitive for an academic faculty position; and in a circular fashion, it would be expected that many of the individuals who have the research and training excellence to obtain a faculty position would be the same as those who have the research and training excellence to publish in a CSN journal or obtain competitive funding. Our conclusion is not that these funding or publication accomplishments are unrelated to obtaining an academic faculty position nor that these accomplishments are not looked upon favorably in the hiring process. What the data above clearly demonstrate, however, is that neither funding nor a CSN paper are necessary to obtain a tenure-track faculty position. In part II below, we provide insight gained from interviews with six individuals at a diverse set of institutions as to what is the most important for obtaining a tenure-track faculty position.

The fifth myth pertains to the belief that one needs to obtain funding or a CSN paper to transition out of an intermediate position into a tenure-track faculty position. Of the 182 individuals in this group, 55% obtained funding and/or published a first-author CSN paper during their intermediate position (i.e., after completing their postdoctoral fellowship period). Conversely, 45% did not. Thus, inasmuch as 72% of individuals who transitioned from an intermediate position had funding or a CSN paper before obtaining a faculty position, almost half got their position without obtaining one of these major accomplishments during the intermediate position and more than a quarter of this population transitioned to a faculty position without having obtained competitive funding or a first-author CSN paper at any time. These data demonstrate that one need not obtain one of these accomplishments during the intermediate period, or indeed, at all, to obtain a tenure-track position.

Although not in direct response to addressing the myths, additional interesting information emerged from the data. We found it remarkable how many institutions represented by our cohort hired individuals into tenure-track positions that had previously been trained or employed at that institution. Across the entire cohort of 133 hiring institutions, 55% hired one or more individuals that were known to it by previous training or employment. Among the individuals hired, however, this behavior was markedly more apparent for those who transitioned to an intermediate position between their postdoctoral fellowship and tenure-track position. Whereas 58% of those hired out of intermediate positions were hired by an institution where they had previously trained or worked, only 23% of those who transitioned to a faculty position directly from their postdoctoral position were hired by an institution where they had previously trained or worked.

Another interesting finding was that, of the 344 members of the entire cohort, only 27 individuals were hired into tenure-track positions after transitioning to a non–tenure-track position outside of their postdoctoral institution. With the usual caveat that we do not have a control group to evaluate the success of individuals who pursue this pathway, these data indicate that taking an intermediate position outside of the postdoctoral institution is not a common route to a tenure-track position.

Part II: Statements by six individuals who have overseen much hiring regarding what they and their search committees look for during the hiring process

The data in part I demonstrated that, although undoubtedly a beneficial addition to a CV, one does not need a K99/R00 award, funding of any sort, or a paper published in the CSN journal family to obtain a first tenure-track faculty position. Given that none of these specific prefaculty accomplishments are necessary for obtaining a faculty position, we sought to determine factors that were. To address this, we interviewed six individuals who have a long history of being involved in, and overseeing, the hiring process. We selected these individuals on the basis of their stature at their institutions, their extensive experience in hiring faculty, and their being at six different types of institutions. We posed two general questions to these individuals: (i) “What characteristics are you looking for in order to invite somebody for an interview?” and (ii) “what factors lead you to hire somebody, and what issues lead you to not hire somebody after you’ve interviewed them?” After posing these questions, we did not ask for discrete answers to these specific questions but rather asked those interviewed to talk to us about the factors that are most important in the hiring process. Below, we have used either direct quotations or paraphrased answers to provide a brief, descriptive answer. Before submission of this paper for publication, we sent it to each of these individuals to confirm the accuracy of the statements or thoughts that we attributed to them (bolding was added by us for emphasis, and confirmed by the individual interviewed as appropriately applied).

Diane Lipscombe, Ph.D.

Thomas J. Watson Sr. Professor of Science

Reliance Dhirubhai Ambani Director,

Robert J. and Nancy D. Carney Institute for Brain Science

Department of Neuroscience

Brown University

Providence, RI

We are looking for the potential to succeed in research. We don’t use a K99 as a way to triage anyone. A K99, or any other funding, is of secondary importance. We also don’t look at numbers of papers, but at their quality. We do look at the journal name, but we also look at the paper itself. A short paper in a high-profile journal is often less interesting, and less of a draw to us when hiring, than a solid scientific contribution. We value this much more than many papers that are parts of studies— we are looking for solid research pieces that demonstrate independence and creativity by the candidate.

We like to see consistency in someone’s CV. We’re looking for high quality, consistent, rigorous research. We look closely at letters of recommendation. And we look at the research statement quite deeply, which is a very important factor in choosing who to interview.

We require a statement from applicants on diversity and inclusion. In recent hires, we’ve read that first. This doesn’t mean that the person has to be an underrepresented minority. We’re looking for a sincere, demonstrated interest .

We’re looking for independence and passion, although that can be hard to define. Someone who isn’t passionate about education and mentorship won’t be happy here. This doesn’t mean we require formal teaching experience or a teaching certificate. This teaching experience can show up in a multitude of ways, even as an interest outside of your research—for example, community outreach.

Things that are turn-offs? Lack of a particular interest in Brown. We want the applicant to have thought about how they’ll interact in our community.

To get on the shortlist , the cover letter will tell you a lot about the effort they’ve put in. Do they know the faculty at Brown and how they would fit in? Video pre-screens also give us information about their interest in Brown, their understanding of their own work, how they view the impact of their work, the challenges they see in their research.

Networking does have an influence. A letter from a faculty member we know, whose opinions we value and who we know is completely honest in their assessments, counts.

At the interview, their knowledge of their work can come through in a presentation, but the chalk talk is where we really learn about their understanding of their work and how they see their work intersecting with the faculty here .

Ted Abel, Ph.D.

Director, Iowa Neuroscience Institute

Chair and DEO, Department of Neuroscience and Pharmacology

Roy J. Carver Chair in Neuroscience

Carver College of Medicine

University of Iowa

Iowa City, IA

We are looking for a colleague who is intellectually curious . This comes from an ability to ask insightful questions and to use techniques that are appropriate to answer those significant questions. Having a hot new technique is not sufficient without knowing important and interesting questions that can be addressed with these new approaches.

Funding and journals count but are not the key issue. We’ve known applicants with a K99 and a CSN paper who couldn’t articulate the importance of their research, so we don’t base decisions solely on funding and the journals in which research is published. One aspect that is important is consistent productivity at a high level throughout a candidate’s graduate and postdoctoral work.

We want to know that the candidate is driving their research project, and we seek individuals who understand the importance of their work, the strengths and weaknesses of their technical approaches, and have a sense of where the field is headed.

We’re interested in people who have thought about what big questions they’d like to address and how they might study them in their own lab. What would they pursue that might make it into the textbooks? How would their research make a difference either in our fundamental knowledge of neuroscience or how we might better understand brain disorders.

The research statement is very important, and it should not read like it was copied from an NIH Biosketch or a Specific Aims page. The research statement should clearly and concisely describe the advances that the candidate has made in their research and outline where they are headed. A “graphical abstract” as a part of this statement can make things much clearer. The cover letter and CV can break an application but can’t really make it. The research statement can make it.

Community matters. The best neuroscience is carried out by collaborative communities of faculty, fellows, and students. As faculty candidates look at potential institutions in which to launch their careers, it is important to look closely at the neuroscience community at the institutions you are considering. Are faculty appropriately mentored? Are students and fellows part of a collaborative community that supports their training? Find out about faculty whose research connects with yours and determine if there are appropriate resources to help you grow your research program. Our search committee looks for candidates who have sought answers to these questions.

We all focus too much on metrics. Just because we can measure things does not mean that they are important or significant. We seek to focus on the unique strengths of individuals to identify their potential to make discoveries in their lab in the future that will make a difference in how we understand how the brain works.

Joseph LoTurco, Ph.D.

Department Head and Professor

Physiology and Neurobiology

University of Connecticut

Out of 150-200 applications, we usually whittle down to 20-25 for a remote interview by grants and publications. We are mainly interested in 1) someone who wants to be in our department, wants to work with our people, in our kind of environment, and 2) someone who will be successful in getting tenure here. But we don’t typically get to these issues until we get down to the 20-25.

We don’t care too much about what graduate school or postdoctoral institutions people come from.

For the first cut, we look at where they’ve published as an indication of quality of work. We do not require CSN publications. We are looking for top-field journals. We are also looking for a CV that is not filled with short papers. Once the first cut is made, we will go back and read some of the papers. We have hired plenty of people who don’t have CSN publications. In fact, we may actually be a bit suspicious about a CSN publication vs. a 2-3 author paper in a really good field journal. We look for balance. Almost all of the applicants we look at have 8-10 papers minimum. Probably 3 of those will be first-author or communicating author papers. We are looking for at least 2 to be in really good field journals and at least one to be during their postdoc (recent).

The vision for their research is really critical. They need to prove that they have a real idea of what they want to do and that it is going to excite a group of 4-5 people, including people who aren’t experts in their area.

There is typically a noticeable difference between a candidate who has at least written a research grant and those who have not. This becomes particularly evident in the chalk talk portion of the interview. You can also tell which applicants have written grants because their research statements are much more polished.

At the Skype interview, we get a general sense of whether the applicant knows what they are going to do. That probably whittles the pool down to about 10 people. They have to demonstrate that they own their research and have thought about it. People still answer questions factually wrong at this level—that will sink them. The other critical thing we ask is, “why do you want to come to our institution and our department?” Some people can’t answer this; eliminates 2-3 people every round. A lot rides on this initial Skype interview.

Once we narrow applicants down to an interview list of 10 people, grants and publications become less important ; we actually don’t find that having a K99 is a huge predictor of success when they get here.

We are looking at how well they communicated in their talk—it’s a diverse audience—undergrads, grad students, lots of people that aren’t in their field. They have to be able to communicate well. The buzz in the hallway after a job talk takes on a life of its own. Then, we do a chalk talk. We also want to make sure that the applicant is conscientious about teaching.

Leslie C. Griffith, M.D., Ph.D.

Nancy Lurie Marks Professor of Neuroscience and

Director of the Volen National Center for Complex Systems

Department of Biology

Brandeis University

Waltham, MA

The people who have been successful here are people we chose because they fit us. This will be very different than a very large department, which looks for a different kind of fit. We are high quality but small. We look for someone highly collaborative, who extends boundaries but isn’t separate from the core group. People that are scientifically diverse end up having really good interactions, because they’re imaginative . Candidates need to do their homework, figure out what people work on, be interested, and collaborative. We want to see that they will be able to get along with the department .

We look really carefully at publication record as well. We value someone who shows judgment in their publications as a postdoc . An 8-year postdoc with 1 Cell paper with 10 authors—that is a red flag to us … it shows terrible judgment. There are 4-5 papers worth of data in that Cell paper. We look for someone who published in a distributed manner with some high-profile papers (i.e., in “good” journals) but with also some solid work in what some people may consider “lesser” journals—but still good science.

My process is to look at the CV, papers, where they are publishing, what the topics are. Then, I look at the research statement. They have to convince me in a 4-page research statement that what they did was important, sound, interesting. The research statement makes a really big difference and the letters of reference do, too . If I’m really interested, I’ll go back to the papers. I have confidence that if a paper is published in a reputable journal, it was adequately reviewed. It’s the person’s plans, ideas, and way of expressing themselves that make a difference .

They should have a strong letter from postdoc mentor, graduate mentor, and maybe a collaborator letter . You can tell when someone writes a letter and they don’t really know the person. It’s bad when somebody has a letter from someone who doesn’t really know them. That rings false.

Communication matters. The 5-minute pitch, the ability to respond to questions without panicking is important . They have to be able to give a good talk that will not only engage neuroscientists but biologists, psychologists, biochemists, physicists, etc. I would say, though, that the chalk talk is the major separator. Some people give beautiful presentations but go down in flames during the chalk talk.

Marc Freeman, Ph.D.

Vollum Institute, OHSU

Portland, OR

Creativity is an invaluable commodity that can serve a person in science their whole life. I personally gravitate toward applicants where I read their package and learn something new and interesting, and I get convinced that there’s room for a lot of exciting and important questions to be explored. With the assumption that the science will be high quality, novelty is a big deal . Even before looking at the papers, we want to know whether an applicant is looking at a really interesting biological question. The good science always wins out. Usually that means the funding follows.

One doesn’t need a paper in a so-called “high-profile” journal to be competitive, but having papers only in lower tier journals probably won’t cut it. Very interesting, well-done science that appears in highly respected journals will do it. It is important to see that the candidate has been successful at each career stage—history will repeat itself when they are PIs.

Grants and papers are nice, but certainly don’t guarantee anything. One gets the interview based on what they’ve done and how they’ve presented it to us in their application. Did we get excited enough to offer them one of a limited number of slots to visit? Having funding is unimportant. If somebody is doing novel, interesting, important research, we can then help them get funding. It’s our job to mentor them to help them get funding. I don’t see a lack of current grant funding as a problem at all. In fact, many people that get funding like K awards do so because their PI basically writes it with them. It’s not necessarily a reflection of the candidate’s ability to get funding.

We want to be convinced that the person is excited to join us. Would they look forward to being here and why? Does their reasoning make sense? Not all people are a great fit for us, nor our environment a great fit for them. The match is key.

One ultimately gets hired by convincing us that they’ll do something interesting and that the ideas are the applicant’s (not just fed to them by their boss) . The chalk talk is the most important part of the visit. Anybody can give a polished presentation given enough practice. The chalk talk is where we see their understanding of their work, creativity, and ability to make a compelling argument.

We’re looking for the kind of person who has the disposition to run a lab; some don’t, so we’re also looking at management potential. You want someone who’s going to be comfortable working with a whole lot of people and personality types and can inspire them to work hard. If someone comes into an interview and has bad interactions with faculty or doesn’t interact well with trainees, that’s a red flag.

Networking is important. An applicant will be helped if someone on our faculty knew them, heard them give a talk, or met them somewhere. It can really help. It will help get them through the door. It’s important to be known in your field even before you are a PI. You can get a lot of credit in your application if people who are outside your immediate orbit and who have no vested interest in your success are vouching for you in recommendation letters. I encourage my postdocs to get to know PIs at other places and build relationships. These types of references indicate that you have started to gain the respect of your field.

Matthew N. Rasband, Ph.D.

Professor and Vivian L. Smith Endowed Chair in Neuroscience

Baylor College of Medicine

Houston, TX

We do not use funding as a litmus test for any applicant that we’re interested in, it’s simply not one of the major criteria. If a person has a K99, great—we view it as a bonus—but it is not considered as a requirement.

I am interested in applicants who can demonstrate continued and sustained high productivity, regular publishing of papers. In the neuroscience field—if I saw one applicant with 1 CSN paper and another applicant who had 3 papers in a top tier journal, I would go for the one with three papers in a heartbeat. I am far more interested in people who show and demonstrate that they know how to “walk the walk” and “talk the talk” again and again. That is the most important criterion—continuous, sustained productivity. I want to see that they’ve climbed the mountain, gotten to the top, and started to climb another mountain, over and over. Some mountains will be higher, and some lower. But I want to see that hungry to climb mountains.

In fact, it is a bit of red flag if I see only CSN papers—because I wonder whether their perception is that early on in their faculty position they have to publish in big name journals. That may be their personality or possibly their experience in their prior labs. My impression is that, as faculty, they often waste time spinning their wheels going through reviews only to be rejected by the vanity journal and then they go to their perceived lower journal. They could have spent that time starting another project (“climbing up another mountain”).

During the hiring process, we ask the committee to come up with their top 6-10 applicants and then we look at their research statement . What is their vision for what they want to do? How would they fit in the department? We are interested in looking for the very best scientists and people who have the best vision and ideas, who can clearly articulate what they want to do, and why they want to do it. It is a subjective evaluation, but if somebody can write a really compelling vision in their research statement, that puts them way ahead.

There should be at least a couple of labs that a candidate can work synergistically with and collaborate with . I want someone who I could talk with to bounce ideas off of each other.

Frequently, many of the top candidates we get are from colleagues who we know through previous interactions. The best cases are where there are outstanding people, who are reaching out, and their mentors are reaching out—mentors reaching out is very important, maybe more important— it does matter who the letters are from. If the letter is from someone who we know and trust, the letter carries more weight .

Applicants can cold-call, but a more effective strategy is if you have a mentor that has relationships with chairs and deans that can reach out. The mentor can have much more of an impact that the applicant cold calling themselves.

The most important component of the interview for me is the chalk talk —it is the thing that always sells it. Candidates have spent years thinking about their particular projects, so if they can’t knock their presentation out of the park, that is an obvious problem. But can they stand up at a chalkboard, respond to faculty questions and defend their ideas? We want to know what it is that they cannot wait to get into the lab to do: we want to know their vision. The chalk talk is the deciding factor.

Summary of senior academic faculty interviews on hiring new faculty

The six individuals selected for these interviews represented a variety of types of research institutions. The institutions ranged in size from large to small; some were affiliated with medical schools and some were not; some were public institutions and some private. A common feature among all, however, was excellence in research and a high expectation on faculty to obtain major grants to support their research as faculty. Our interviews suggested that, whereas funding and papers in prestigious journals can play a role in hiring, individuals doing the hiring are fundamentally looking for thoughtful, highly creative, and well-trained individuals who are in pursuit of novel discoveries, fit well into their departments, and are well-suited to personal interactions with people that have different perspective and experiences. Critically, all of those interviewed placed a high value on an individual being the driver of their research, a person with a vision for where their work will go in the future, and a sense that the work will be important. All stated that one of the most important components of an interview was the chalk talk in which the applicant needs to be able to discuss their research ideas and answer potentially unexpected questions from faculty that may be experts or may know nothing about their field. A clear negative is where the applicant is perceived to have been working on the mentor’s research, with a lack of clear vision of how they themselves will contribute something new.

In the current paper, we set out to address some of the frequent myths that we hear at NINDS about perceived metrics of success to obtain a tenure-track faculty position. We used a data-driven approach that examined the funding history and publication record of NINDS ESI R01 applicants who obtained their first tenure-track faculty position during the K99 era. We found that, whereas a history of funding and publication in high-profile journals may be beneficial to an applicant, these factors are not necessary to be successful in the academic job market. Comments by some of those we interviewed suggest that caution should be applied to the pursuit of a CSN paper. Certainly, there may be individual departments that require applicants to have funding, or potentially a CSN publication, to be considered for hiring. J. LoTurco at the University of Connecticut stated that this was an important factor in an initial screen of applicants. Overall, however, 82% of the institutions that hired an individual in our cohort hired somebody who did not have funding before being hired, and 60% of the individuals hired did not have prior funding.

On the necessity for funding and/or CSN publications to obtain a tenure-track faculty position

Trainees with transition funding receive more job offers ( 1 ) and virtually all NINDS K99/R00 awardees obtain independent research positions. However, the number of K99/R00 awards is very small relative to the number of research positions available. The key point, however, is that inasmuch as most K99/R00 awardees obtain independent research positions, few who obtain academic positions had a K99/R00 award.

Similarly, whereas just over half of the individuals in our cohort had a first-author CSN paper before obtaining a faculty position, nearly half did not. Consistent with our data, a survey study by Fernandes et al. ( 1 ) suggested that neither funding nor publication metrics were able to distinguish between those who were hired into faculty positions and those who were not. A study by van Dijk et al. ( 2 ) suggested that publications in high impact factor journals could be used to predict success in becoming an academic PI. These findings are not inconsistent with ours based on a similar distinction as that made between K99/R00 awardees getting positions and needing a K99/R00 award to get a position. It is not unusual that individuals with one or more outstanding publications in a high impact factor or high visibility journal are highly competitive for academic positions. Our data support this conclusion, in that approximately half of our cohort had first-author CSN publications. Our data demonstrate, however, that such publications are not necessary to obtain a faculty position in that approximately half of those hired did not have one. Similarly, a survey study by Martinez et al. ( 3 ) suggested that publication in a high impact journal was relatively unimportant relative to other factors in the success of underrepresented minorities obtaining faculty positions.

Knowing you and your work firsthand appears to play an important role

Our data suggest that there are other factors beyond the scientific accomplishments of the individual that can also play a role in obtaining a faculty position. For example, 41% of our cohort was hired into an institution at which they had previously conducted research (i.e., where they were known). This was apparently more important for individuals who took an intermediate position between the postdoctoral fellowship and the tenure-track faculty position than for those who transitioned directly from postdoctoral position to the faculty position The basis for this latter distinction is beyond our ability to explain with our data, as most of the individuals who took intermediate positions did so at their postdoctoral institution. Perhaps related to this, previous studies have shown that the doctoral institution at which individuals train is a factor that influences the competitiveness of an applicant for an academic position ( 4 , 5 ).

Previous studies also found a relationship between the career support a postdoctoral advisor provides and the likelihood that an individual would obtain a tenure-track position ( 3 , 5 ). One might surmise that this support can go hand-in-hand with providing strong recommendations and even proactively promoting candidates for faculty positions, which some hirers we interviewed stated as strong indicators for selecting candidates for interviews.

The focus on scientific vision, quality, and potential for collaboration

The results of our study are consistent with an opinion piece by Martin ( 6 ) on tips for obtaining a faculty position. To summarize, a broad set of factors is involved in obtaining a faculty position. There is no question that publication of high-quality science is important. Moreover, one can surmise that publications in high-profile journals and obtaining funding can be beneficial (but see caveats suggested in part II above). However, our data clearly demonstrate that neither publishing in high-profile journals nor obtaining funding during training periods are required. Moreover, the faculty interviewed in our study indicated that they valued a few significant papers (significance relating to the science, not to the prestige of the journal) over many shorter, less important papers. Our data, together with the information gained from interviews, indicates that doing high quality science, being able to articulate a vision for your science, owning a project that serves as a starting point to realize your vision, communication skills, and personal fit within an environment are all key factors in obtaining a faculty position. On the basis of both our data and interviews with hirers, accomplishments such as competitive funding or publication in a CSN journal, although likely beneficial, are not necessary.

Last, there is a growing understanding of the importance of diverse viewpoints and perspectives to scientific progress, such as the benefits of bringing diverse perspectives to innovation and problem solving ( 7 – 9 ). In line with these findings, several of the hirers we interviewed described an increased emphasis in the hiring process of seeking individuals who valued and/or provided a larger diversity of perspectives.

Confidence in the approach we used to answer the questions asked

Ideally, to do the analyses in part I of this paper, we would have had a list of all neuroscientists hired into tenure-track positions in a given year. To our knowledge, such a list does not exist. We created a cohort from a complete, defined group of individuals who recently obtained tenure-track positions and asked what accomplishments they had before being hired. Although our cohort creation did not depend upon any assumptions, our approach benefited from the knowledge that virtually all individuals who were supported by a K99/R00 award and transitioned into tenure-track assistant professor positions applied for an R01 within a few years of starting their faculty position. Of course, our cohort included only a subset of those hired during the specified time period, but this limitation likely led to an overestimate of the role of funding and publishing in high-profile journals in obtaining a faculty position. For example, many are hired into tenure-track faculty positions that do not have an expectation of applying for an NIH R01 or equivalent. These might include individuals who took faculty positions at smaller institutions, such as liberal arts institutions, who would not frequently be applying for R01s. Similarly, we did not include individuals who have applied for smaller NIH awards (e.g., R21, R03) or individuals whose work is well suited to nonbiomedical research funding. We consider it is unlikely that these individuals have a higher rate of pre-hire funding or CSN journal publications than our cohort. These assumptions are supported by the fact that 96% of NINDS R00 awardees apply for an R01 by the end of their 3-year R00 grant period; we would not have missed a lot of individuals who had K99/R00 funding by not including these other groups.

Our cohort was limited to a 3-year window of application to NINDS and did not include individuals who applied to other NIH institutes for their funding. However, there is no basis for believing that the results would be fundamentally different had we chosen a different set of grant application deadlines or included neuroscience applicants to other NIH institutes. Moreover, because of the ease of collecting the information, we expanded our K99/R00 analysis to both a 5-year window of applicants for an NINDS R01 and to include NIs and ESIs. Even with this expansion to almost 1000 individuals who applied for their first NINDS R01 over a 5-year period, the upper limit of the percentage of tenure track faculty hired during the K99 era remained at 11%.

We chose the six faculty members to interview on the basis of their experience in hiring individuals into neuroscience faculty positions at different types of institutions. One can reasonably ask whether these six institutions represent a larger number of hiring institutions in the country. Two observations suggest to us that the answer is yes. First, the six hirers we interviewed independently provided remarkably consistent descriptions of critical issues for hiring an individual into a tenure-track position. Second, the expressed lack of importance placed on funding by five of six of these individuals is supported by our data that 82% of institutions in our study hired an individual who did not have prior competitive funding.

Our approach was intended to directly address the myths that we framed. We did not seek to determine what accomplishments provide a competitive advantage for obtaining a faculty position nor did we address whether one accomplishment was more important than another. Our goal was to address the very pervasive myths that we hear almost daily that relate to whether certain accomplishments are needed to obtain an academic faculty position. Postdoctoral fellows often feel quite stressed about the perceived need for a K99 to obtain a faculty position. We at NINDS have known since the initiation of the K99 award, simply by knowing who is applying for NIH grants, that this myth was not true. The pervasiveness of these myths is potentially damaging in several ways: (i) It might cause trainees to focus on these metrics of accomplishment rather than their training and the pursuit of important scientific questions that might not quickly turn into publications in prestige journals or funding opportunities, (ii) it may discourage trainees from pursuing academic faculty positions because they feel they have not fulfilled these perceived requirements, (iii) it can mislead trainees regarding their understanding of what is important for their future, and (iv) it can put undue, and unnecessary, stress on trainees who believe they must achieve these specific metrics of accomplishment. Equally damaging, in our view, is the potential for prolongation of time in graduate school or postdoctoral training that occurs for some based on the belief that their work must be published in a very prestigious journal to be competitive for a faculty position. This focus on journal prestige or, similarly, on the importance of obtaining competitive funding during training, can lead trainees to miss opportunities to obtain critical skills and broad education that their time in a training position allows them the time to explore and that will benefit them greatly in the long run. This was reinforced through our interviews with hirers, all of which placed great emphasis on applicants having a clear vision and passion for their science, a detailed understanding of both the technical aspects and significance of their project, and an understanding of how they might fit into a new scientific environment. Not only were funding and publications in prestigious journals not critical factors for obtaining first faculty positions at five of six of the institutions we interviewed, but it was also pointed out quite clearly that excessive pursuit of a very high-profile paper at the expense of steady publication of important work may be viewed by some as a negative.

MATERIALS AND METHODS

Data sources.

Data were obtained from the Information for Management, Planning, Analysis, and Coordination (IMPAC II) database, which is used by NIH staff to track and manage grant applications and awards. Most of the data were manually extracted from the NIH biosketches included with grant application submissions. When biosketches did not contain key information or lacked adequate detail, data were sourced from other repositories of publicly available information including departmental and laboratory websites, PubMed, LinkedIn, and Twitter.

From these collective sources, we were able to ascertain the following for all individuals in the study cohort:

1) The positions held and the time spent in each position from matriculation into graduate school to the start of the tenure-track or equivalent position. The positions considered were graduate student, “postdoctoral positions” (positions that start immediately after obtaining a doctorate, often called “postdoctoral fellows”), and what we termed intermediate positions before beginning the assistant professor (or equivalent) position (see below for definition of intermediate positions).

2) Funding history (including NIH F32, K-series and R-series grants, and non-NIH grants).

3) Authored publications before the start of the faculty position. For each publication, we identified the journal, whether the individual was listed as first author (including co–first author) and whether the paper was published from work performed during graduate school, postdoctoral training, or the period identified as within an intermediate position (papers that included the predoctoral advisor as an author were considered to have been associated with graduate school and papers that included the postdoctoral advisor were considered to have been associated with the postdoctoral period).

Data analysis

Data were organized in Excel for the basic descriptive statistics performed in the study. No inferential statistics were performed as the intent of our study was to determine whether certain accomplishments are required to obtain an academic faculty position, not to ascertain statistical differences in the prevalence of accomplishments by different groups of individuals nor to determine what accomplishments might make one more competitive for a position.

Intermediate positions

We defined intermediate positions as those that occur subsequent to a postdoctoral fellow position and before starting the tenure-track or equivalent position. Titles in our cohort included: research assistant professor, instructor, research associate, adjunct assistant professor, assistant professional researcher, assistant project scientist, assistant scientist, lecturer, research investigator, research scientist, and staff scientist.

Acknowledgments

We thank E. Marder who read an early draft of the manuscript and provided very helpful suggestions. Funding: The authors acknowledge that they received no funding in support of this research. Author contributions: N.S.H., K.P.R., M.S.T., and S.J.K. were involved in study conception, design, and manuscript editing. N.S.H. and K.P.R. carried out all data collection, analysis and data visualization, and wrote the initial draft of the manuscript. S.J.K., N.S.H., and K.P.R. conducted the interviews and interpreted the data. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper.

View/request a protocol for this paper from Bio-protocol .

REFERENCES AND NOTES

Volume 15 Supplement 2

Accomplishing Career Transitions 2019: Professional Development for Postdocs and Tenure-track Junior Faculty in the Biomedical Sciences

• Open access
• Published: 22 June 2021

Preparing for tenure at a research-intensive university

• Michael Boyce 1 &
• Renato J. Aguilera 2  

BMC Proceedings volume  15 , Article number:  14 ( 2021 ) Cite this article

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At research-intensive universities in the United States, eligible faculty must generally excel in research, teaching and service in order to receive tenure. To meet these high standards, junior faculty should begin planning for a strong tenure case from their first day on the job. Here, we provide practical information, commentary and advice on how biomedical faculty at research-intensive institutions can prepare strategically for a successful tenure review.

Introduction

New tenure-track faculty members at research-intensive (R1 or R2) institutions [ 1 ] emerge from a competitive, months-long job search process, eager to begin their independent careers. At this early stage, the tenure process may seem far away – about 6 years at most institutions – but tenure-planning should begin as soon as possible. Of course, being a new faculty member comes with a steep learning curve. Nobel Laureate and former Howard Hughes Medical Institute President Tom Cech has likened this to getting a driver’s license: “All of a sudden you have all of this freedom to turn when you want to turn or to go straight when you want to go straight. On the other hand, you have to pay for the gas, and you’ve got some responsibility” (quoted in [ 2 ]). How to balance the day-to-day tasks of a brand-new faculty member with the long-term career-planning you need for your future? This special issue of BMC Proceedings contains other valuable articles on managing the specific and immediate challenges of your new job, such as how to set up a research lab [ 3 ]. Here, we focus on the longer-term strategic planning that you need to position yourself as a shoo-in tenure case.

Know the rules of the game

The crucial first step in preparing for tenure is to understand the processes and expectations at your institution, for your position. Tenure requirements at American R1/R2 institutions change over time. Generally speaking, faculty in the 1980s were expected to demonstrate excellence in research, teaching or service, but 20 years later, all three came to be essential, with research as the top priority in most cases [ 4 ]. Promotion and tenure criteria also vary by institution and can sometimes be frustratingly vague [ 4 , 5 , 6 , 7 ]. Ambiguous or general criteria can be good, insofar as they allow for flexible and holistic assessment of each candidate, but they can also be bewildering for new junior faculty, who crave clear expectations. First, get the official tenure and promotion guidance in writing from your institution. Often this is publicly available in a faculty handbook or similar document from the Provost or equivalent chief academic officer. Read the guidelines carefully and then discuss them with your network – your department chair, senior colleagues both inside and outside your department, recently tenured faculty and (ideally) colleagues who have served recently on appointment, promotion and tenure (APT) committees. Ask questions about anything that’s unclear and solicit advice about any “unwritten rules” that you should know, such as the relative weight placed on research, teaching and service at your institution. Many universities have Faculty Advancement or equivalent offices that offer workshops on tenure preparation for junior faculty – attend every year, to track any changes in expectations and to keep the goal on your radar. In short, know the rules. All of the advice that follows in this article is based on common themes among research-intensive US universities and our own experiences, but we stress that all tenure processes are local , and you must do your due diligence to learn the ropes and expectations at your own institution.

Know the process

To get tenure, you’ll need to know what goes into a successful tenure dossier and how it is evaluated [ 8 ]. You can expect that your research, teaching and service accomplishments will be comprehensively assessed. For research, peer-reviewed publications (especially primary research, but also reviews and commentary) and grant funding are key. For teaching and mentoring, teaching philosophy, syllabi, course evaluations and other documentation are typically required, and lists of trainees in your lab and service on thesis committees are the norm. Service is generally given the least weight, but notable accomplishments in the outreach, science communication, public policy, mentoring, and diversity/equity/inclusion (DEI) realms are valued, provided they accompany strong research and teaching. We discuss each of these three areas in more detail below.

Learn the nuts and bolts of the tenure preparation process, including the timeline. For example, you may undergo a pre-tenure review after your third year or so. At this stage, you typically prepare the same documents as you would for tenure (but without external evaluation letters; see below) and members of the departmental or APT committee review this package. You’ll receive feedback, focusing on areas of weakness and offering advice for improvement. The committee may even recommend an early tenure process, in strong cases. Typically, a complete dossier will then be due to a department chair by the end of a faculty member’s fifth or sixth year on the job. It often gets a first-pass read by the chair and an ad hoc departmental committee, to generate a list of external reviewers whom the chair will invite to provide letters reviewing your tenure and promotion credentials. Once letters arrive, the departmental committee evaluates the case thoroughly and presents a recommendation to the department (usually tenured members only) for a discussion and vote. After that, the chair usually shepherds the case through next steps, including review by a school or college APT committee, a dean, a University-wide APT committee, the Provost and the President or Board of Trustees or Governors. Get clarity from your department chair about when your dossier documents will be due, how long the process takes after submission (typically 6–12 months), and whether you can provide updates along the way, such as late-breaking grants or accepted manuscripts.

In your first months on the job, learn what future milestones you’ll pass en route to preparing your tenure dossier. Will you have annual evaluations or reappointments by your chair, a committee or someone else? Will an official mentor or mentoring committee of senior faculty be appointed for you (or will you need to request one from your department head or organize it yourself)? Is there a mid-tenure review after 3 years or so? These examples illustrate structured ways to receive feedback on your progress even in early years, so seek out these opportunities if they’re not provided automatically. If your institution requires your CV in a particular format for the tenure dossier (which is common), ask for a template in your first month on the job and begin adding to it right away. To start, list everything, even seemingly small accomplishments or honors, such as invited talks at your own institution, 1 hour of service on a panel discussion or a blurb highlighting your recent publication in a different journal. Down the road, you can always trim some items from the CV if you like, but you can’t add what you can’t remember, so don’t rely on memory and keep the document updated in real-time. Another strategy is to keep a tenure folder in your desk drawer, containing information to be added to your dossier at a later date, such as seminar fliers of your talks, thank-you letters for services provided, invitations for paper and grant reviews, service on committees, etc. You may be surprised how much you’ve done after five or 6 years and how many things you would have forgotten if you didn’t keep this information in one place.

Mentoring and training undergraduate and graduate students are important not only for your research (see below), but also for your tenure evaluation at most institutions. As you prepare your tenure dossier, consider adding a mentorship statement that describes your training record [ 9 ]. For example, do you offer hands-on training in your lab yourself? Do you teach or participate in workshops, such as NIH Responsible Conduct in Research or Rigor and Reproducibility trainings? Do you teach manuscript- and grant-writing to mentees and others? Do you perform outreach to recruit students from historically excluded groups to your university? Be sure to mention if you’ve received formal mentorship training by your institution or a professional organization, such as the National Research Mentoring Network. Within your academic lifespan, you’ll train a significant number of students and it is therefore important to keep a record of these trainees and their whereabouts and accomplishments (publications, fellowships, invited talks/presentations, etc.). You can also track former trainees by asking them to create a LinkedIn or ResearchGate account while they are under your supervision. At one of our institutions (UTEP), we expect all undergraduates in our NIGMS-funded training programs to create LinkedIn accounts so that we can stay current on their achievements and facilitate our own grant progress reports, renewals and new submissions. If your trainees move on to great places to pursue their post-graduate careers, you should list that information in your CV or mentorship statement. This information will also be valuable for NIH training grant applications, which require you to list your mentorship accomplishment in your biosketch and trainee tables. Importantly, some institutions request letters from current or former trainees as part of the tenure review process, providing another good reason to be the best mentor you can.

When it’s time to write your tenure dossier documents, keep your multiple audiences in mind. Usually, a single research statement will be evaluated by a wide range of groups, including the colleagues in your department, experts in your specific field (i.e., the external letter-writers) and non-scientists, such as German or law or divinity faculty on a university-wide APT committee. Writing a document that’s accessible and exciting to all of these audiences is a challenge, and it pays to get lots of feedback on drafts from friends or colleagues in each of the above categories. In planning your document, it can help to begin with a broad and non-technical overview of your research and its significance in the field, to help orient non-scientist readers, and then work down to specifics and expert knowledge when showcasing your science for others in your specialty.

External letter-writers can be the most mystifying (or terrifying) audience for your dossier. They must typically be “arms-length” from you, meaning you’ve never trained or collaborated with them, yet also expert enough to evaluate your work, and senior or distinguished enough for their letters to carry weight at your institution. Although you may never learn who the letter-writers are, a department chair or senior colleague might ask you (often off the record) to suggest a few names of prospective referees. If you have this opportunity, name scientists who know and appreciate your work, whose letters will be credible and respected, and whom your department might not think of themselves. If your field has one prominent scientist who is a clear leader, your chair or committee is likely to know that and will invite her or him as a letter-writer themselves, so don’t waste a limited number of suggestions on obvious picks. If you choose to suggest referees from outside the US (e.g., to attest to your international research reputation), be sure that they are familiar with the standards and norms of American tenure letters. If necessary, consider requesting to block one or two scientists as letter-writers, if there are people in your field who are known bad actors or with whom you’ve had a professional conflict. But use this option sparingly and with ample justification, so as not to give the impression that you aren’t well-liked in your field. Whoever your external referees are, you want them to sing your praises and say that you would get tenure at their own institutions, a question they are usually asked to answer.

Finally, a word about changing the process: Institutions usually provide the opportunity to “stop the tenure clock” for specific reasons, such as family care obligations, temporary medical problems or other circumstances (including COVID-19). Choosing this option pushes back the date by which you will need to submit your dossier for tenure review, to account for reduced productivity during a defined period of time. To determine whether stopping the clock could be right for you, find and understand the applicable written policies from your institution and discuss them thoroughly with your chair, senior colleagues and other trusted advisors. It’s important to ask their thoughts on how clock stoppages are viewed at your institution and whether it would be a good tactic for your specific situation. Ultimately, of course, it’s your prerogative to decide.

As noted above, research is nearly always the primary tenure consideration for faculty at R1/R2 institutions [ 4 , 10 , 11 ]. A strong tenure case is built on a strong research program, with a track-record of exciting science, peer-reviewed publications and extramural grant support. Your research must be independent, meaning you should make it clearly distinct from that of your doctoral and postdoctoral advisors. Building on your prior experience and knowledge is good, of course, but you also have to demonstrate your identity as an innovative and independent investigator by moving in new research directions and making impactful contributions to your field. Another way to think about this is as building your own unique brand – become known as “the person who” (e.g., “She’s the leader in transcriptional control of NK cell development,” “He’s the guy who discovered the role of phase separation in subnuclear compartments”). Similarly, collaborating with other groups can be an excellent way to advance your science, but you should do it judiciously. For any collaborative project or publication, your individual and substantive contribution should be clear (e.g., to external letter-writers evaluating your research output), and you should never let an excessive number of collaborations result in scattershot science, such that your lab lacks its own cohesive research focus. For this reason, it might be necessary to include a detailed description of your contributions and those of your students and staff within the tenure dossier CV for each collaborative paper that you published during the tenure period. And when establishing new collaborations, it’s helpful to discuss goals, division of labor and even authorship on future publications up front, to align expectations and ensure the relationship goes smoothly.

When launching your lab, it’s usually wise to start more than one project, or at least pursue multiple independent approaches to one overarching theme, so that not all your eggs are in one basket. At the same time, of course, you must also avoid stretching yourself too thin in the process. It’s often prudent to have a mix of high-risk/high-reward and safer, meat-and-potatoes projects, to ensure that the lab will be productive while also aiming for impactful discoveries. You should be choosy in admitting graduate students, postdocs and staff to your group to work on these projects. Many new PIs are impatient to fill their empty labs with warm bodies and get the science started, but it pays in the long run to wait for the right rotation student or postdoc candidate, and not accept someone mediocre just for the sake of having personnel. The adage “You are your own best postdoc” frequently applies for the first few years of a new lab, when the PI often works at the bench. If your lab budget allows, consider spending money to save time. For example, if you’re hiring a technician, you may want to bring on a more expensive but very experienced candidate, who can work independently and perform managerial tasks in lab, freeing you up for your other responsibilities. This approach may be especially beneficial for brand new faculty, who must usually establish a good research training environment in order to attract top graduate students and postdocs. Similarly, pricey experiments (e.g., CRISPR screens or proteomics projects) can sometimes be a good early investment, as a way to generate preliminary data for future grants and to lay the groundwork for new projects later.

Assuming you’ve chosen a good team of graduate students, postdocs and technicians, you might also take on a few undergraduates to assist them. Many universities have training programs that select some of the best undergraduate students to work in research laboratories and generally provide student stipends and modest research funds. One avenue to recruit graduate students into your laboratory early in your career is to train a cadre of highly motivated undergraduates. In fact, one us (RJA) ran his laboratory with an excellent team of undergraduates, with two of them later joining the lab as Ph.D. students. These early training experiences can lead to the development of undergraduate research training grants that, once funded, allow many more students to participate in research. Participating in undergraduate training can be a rewarding experience, is often highly valued by colleagues and opens the door to research for students undecided about their career paths [ 12 ]. Experienced faculty find ways of linking up undergraduates with graduate and postdoctoral fellows to form highly functional research teams that can be an asset to any laboratory. The graduate and post-graduate mentors not only benefit from having an extra pair of hands to assist them in their projects, but also attain mentoring skills that will be valuable throughout their careers. Of course, it’s important to make sure that undergraduate training activities are viewed positively at your institution and department, and to be careful to accept only a manageable number of students who are committed to doing high-quality research, and not just looking to burnish their resumes.

Peer-reviewed publications are the coin of the realm and the primary metric used to judge research output during tenure evaluation and beyond. Be sure to know what your institution values most in publications. Do you need a certain number? Does the journal name matter? There’s a growing awareness that impact factors are a poor – and often harmful – way of judging research quality [ 13 , 14 , 15 ]. Nevertheless, citation-based metrics, like impact factor, are mentioned in the APT guidelines of many institutions [ 16 , 17 ]. If your university assesses publications using this kind of quantitative metric, it behooves you to understand those rules and make decisions about manuscript submissions accordingly, perhaps in consultation with your chair or other trusted senior colleagues. In any event, target journals where peers and prospective letter-writers in your field will see your work, and always avoid predatory journals [ 18 ]. Submitting manuscripts as pre-prints (e.g., to bioRχiv) can help advertise your work, garner additional citations and even generate constructive criticism from the community [ 19 , 20 , 21 , 22 ]. Primary publications are the cornerstone of your research portfolio and should be your main focus, but influential or highly cited review or commentary articles in your field are also valuable scholarly contributions. Keep in mind that many journals accept unsolicited proposals or even complete manuscript submissions for review articles – if you have a great idea for a review that will fill a gap in the literature or reshape the way your field views a problem, you don’t need to wait to be invited by an editor before you write it.

Funding is a crucial complement to research. Science costs money, and you’ll probably need grant revenue to bankroll your work beyond the start-up phase. In addition, extramural grant support for your lab shows that funding agencies and their peer review panels value your research, so their seal of approval will be viewed favorably from both scientific and financial perspectives by the people evaluating your tenure case. As a brand-new faculty member, it might be wise to apply for career awards from private foundations or similar sources. Your top priority must be to get your lab up and running, but career award applications are often short and straightforward, and can allow you to cash in again on the strong record of postdoctoral research that got you your faculty job in the first place. In the longer term, project-based grants from NIH, NSF, DoD, large foundations or other agencies are the standard way to keep a lab solvent. As always, know the tenure expectations at your institution – if you need a certain dollar amount in support, a certain percentage of your own salary paid from grants or a particular kind of award (e.g., NIH R01) for a strong tenure case, find that out early, so you can prepare far ahead of time for grant submissions, re-submissions and renewals.

To maximize your chances of funding success, take a strategic and multi-pronged approach. Grant-writing can be laborious and challenging, but try to embrace it as a way to crystalize your ideas and align your research questions and plans with your scientific goals. Gathering examples of successful grants from colleagues is a great way to begin. You can also seek out formal grant-writing training, such as from your institution’s faculty advancement office, professional societies [ 23 ] or popular commercial options like the Grant Writers’ Seminars and Workshops [ 24 ]. Ask well-funded colleagues who have served on review panels and take an interest in your success to read drafts of your proposals and provide candid feedback. Begin far, far in advance, so you have time to receive multiple rounds of feedback if necessary and to work with the staff and administrators at your institution on the budget and approval process, which can be lengthy. Success rates with funding agencies are never as high as we’d like, so prepare to take many shots on goal. Some applications may run up against bad luck (e.g., a low payline or a hostile reviewer), so submitting a number of applications to different agencies can be a good way to hedge your bets. Consider being flexible in how you approach your science, taking different angles on different grant applications to appeal to different sponsors, and follow up on the directions that get funded [ 25 ]. In all cases, of course, a grant application needs a solid hypothesis supported by compelling literature and/or preliminary data in order to have a chance at funding, so be sure your proposal will have those components before you commit the time to preparing it.

Teaching may be emphasized less than research in R1/R2 tenure cases [ 4 , 10 , 11 ], but a solid record of quality instruction is nevertheless essential. As always, learn the expectations for how much teaching you must do for a strong tenure dossier, and what evaluation metrics will be used. Many new biomedical faculty at research-intensive institutions are fresh off a postdoc where they had little or no teaching opportunities. Therefore, be proactive in seeking out instruction and mentoring to improve your teaching. You can sit in on senior colleagues’ classes and have them evaluate your own, to provide constructive criticism. Many universities have a Center for Teaching and Learning or equivalent. Taking advantage of the resources, workshops and expert advice from those groups can be invaluable for new faculty, and will demonstrate your proactive effort to capitalize on institutional support for strong teaching. Keep in mind that excellent teaching takes a lot of time, with several-fold more hours of preparation than actual classroom contact hours, especially for new faculty and/or new courses. Evolutionary biologist Joel McGlothlin has nicely captured this point, saying “I found that teaching your first class takes precisely all the time available” [ 26 ]. Be sure to schedule plenty of prep time. If possible, it’s also valuable to make your teaching synergize with your research or other interests – perhaps volunteering to teach a course that forces you to brush up on a field relevant to your own science, or helps you ground your own work in a big-picture context when you write a grant. McGlothlin writes that an “NSF program officer once told me that to write a good grant, I should try to imagine how my research could serve as an example in a textbook. This was so much easier to do after a couple of years teaching evolution to undergraduates” [ 26 ]. Teaching a course in your area of expertise is also a great way to convey your enthusiasm to your students and share personal anecdotes of learning about new discoveries at a conference or how breakthroughs in the field were made. Students appreciate hearing about this human side of science.

Looking ahead to the teaching section of your tenure dossier, find out early what kind of materials you’ll need to include. Teaching philosophy statements, sample syllabi and course evaluations are standard examples. Some universities have well-crafted and universally applied course evaluation systems, and others do not. To ensure proper documentation of your excellent teaching, ask your course directors about evaluations before you begin as an instructor in any class (even for a single guest lecture), and create an evaluation instrument – preferably in cooperation with experts at your Center for Teaching and Learning – if one wouldn’t otherwise be provided. Many tenure reviews also require peer evaluations of your teaching and will look for steady improvements over time, so teaching a new course every semester or quarter is not a good idea. Finally, it’s important to note that teaching evaluations frequently reflect bias against certain categories of instructors, such as women and/or p ersons e xcluded because of their e thnicity or r ace (PEER scientists [ 27 , 28 ]). If you belong to these groups (or even if you don’t!), ask your chair or dean what steps are taken in your university’s APT process to mitigate these well-documented biases. In any event, always look past petty or egregious comments and focus on improvements based on constructive criticism.

Junior faculty can make important service contributions in many realms, such as DEI, public policy, science communication, outreach, curriculum development and academic administration. Service should always complement (and not detract from) strong research and teaching and would rarely be sufficient for tenure alone. However, a track-record of impactful service shows colleagues how you contribute meaningfully to the community of scholars in your institution and can be a valuable component of a complete dossier. Service opportunities exist at the department, school, university, national and international levels, so you’ll want to think strategically about which activities appeal to you the most, will help advance your tenure case and represent a manageable time commitment. Notably, scientific or professional societies can be both a tremendous support for junior faculty and a source of significant service and leadership opportunities beyond your own university [ 29 ].

As a junior faculty member, you’ll want to select your service obligations carefully, such that they align with your values, help your own career and don’t overburden you. Consider saying yes to (or even volunteering for) service opportunities that allow you to contribute to your community while benefitting yourself. One example may be serving on a graduate admissions committee or teaching first-year students, to boost the odds of recruiting excellent people to your lab. Similarly, serving on a seminar-planning committee might allow you to invite prominent scientists in your field who could become reviewers on your grants, papers or tenure dossier, and reviewing a manageable number of grants or manuscripts for funding agencies or journals might be useful experience for preparing your own submissions later. Regardless of your interests, be sure to say no – politely but firmly – to service invitations that would seriously detract from your research, teaching or work-life integration. Junior faculty are usually somewhat shielded from unreasonable service requests, but don’t hesitate to ask for help from your department chair or other mentors if too many demands are made on your time. In particular, women and PEER scientists are disproportionately burdened with service commitments [ 4 , 30 , 31 , 32 , 33 , 34 ]. These requests can arise from good intentions, such as a desire to broaden representation on a committee or a review panel. Nevertheless, women and PEER faculty especially should be mindful of their time and say no to service obligations that would threaten their other work responsibilities. Find out from your chair, mentors or peers what a typical service obligation looks like for junior faculty at your institution, and don’t feel the need to exceed that, if doing so would overtax you.

Organization and time management

Now that you know what you need for a tenure dossier, how can you plan to build a great one? An essential first step is to be organized – when it comes to planning for tenure, “[b] esides productivity, organization is your best friend” [ 8 ]. As suggested earlier, keep your university-formatted CV up to date, starting in your first few weeks on the job, so you’re sure to have complete records of your achievements. Save documentation of your work, too. When you’re finalizing your dossier, course evaluations from a seminar you taught 5 years prior might be impossible to recover, so collect complete and well-organized records as you go.

Time management is also key, in several senses. First, you want to make strategic decisions about how much time to apportion to research, teaching, service and other activities, based on your own preferences and your institution’s priorities. Balancing these interests is a challenge for many faculty [ 4 , 35 , 36 , 37 ], so seek help from your chair, mentoring committees, junior faculty peers, Faculty Advancement offices or scientific societies when you need it. Time management is also critical for accomplishing specific tasks. A postdoc is typically expected only to perform experiments and related work (e.g., writing manuscripts), whereas a junior faculty member faces a huge range of tasks, posing new organizational challenges. Keep a calendar, preferably an electronic one that synchs across all the Internet devices you use. Plan far ahead for major tasks, like preparing a grant or submitting a manuscript. Most junior faculty find that these take far longer than anticipated, from working through multiple layers of budget preparation and institutional approval on a grant application, to wrestling with a journal’s web interface to upload manuscript documents and information in the right order. Try to stay ahead of the game by starting tasks early. Before agreeing to any new commitment (a collaboration, a manuscript review, a new committee membership), be sure to understand the expected time demand and be realistic with yourself about whether it fits well with your availability and priorities. Learning to say no gracefully is both a common challenge and an essential skill.

Some additional advice for fellow procrastinators: It’s helpful to make yourself write at least 1 day a week, even if it’s just for a few hours. Block time on your calendar and write a few paragraphs for a paper, the Specific Aims of a grant, a conference abstract draft, etc. Many PIs prefer to work at the bench versus in the office, but regular and dedicated writing time can help you get the tasks done.

Finally, be kind and reasonable with yourself as you learn the ropes and accept that some things may not get done, or not done quite the way you would ideally want. McGlothlin acknowledges that juggling too many work tasks can often trigger guilt for junior faculty, but it’s possible to come to terms with this:

It becomes hard to focus on getting any one thing done because of the weight of the to-do-list albatross around your neck. I wish I could say that I found some magical time management solution to balance tasks and get caught up, but I never did. What I did realize is that it’s possible to let go of the guilt. You can forgive yourself for not getting things done on time or done as well as you would like, or for prioritizing one task (sometimes the wrong one!) over another. Yes, I still apologize to others when I’m late or otherwise let them down, but I try to forgive myself, cut the albatross loose, and move on [ 26 ].

Professional skills development

New tenure-track faculty at R1/R2 universities often have little formal training for many of their responsibilities, such as grant-writing, budgeting, hiring, managing, motivating and (perhaps) firing employees or students, teaching in a variety of formats, overseeing several research projects at once, complying with safety and ethics requirements on behalf of a group, and a wide range of academic service. Preparing a strong tenure case requires mastering most or all of these professional skills – a daunting task. One strategy is to seek out formal training for junior faculty, such as workshops offered through your institution’s Human Resources, Institutional Equity or Faculty Advancement offices. Some outside groups also offer well-regarded lab leadership courses, such as the American Society for Cell Biology (ASCB) and other professional societies, Cold Spring Harbor Laboratory and the European Molecular Biology Organization (some US training sites are available) [ 38 , 39 , 40 ]. There are also focused programs for new investigators to learn specific skills. For example, several scientific societies offer structured grant-writing programs to new PIs [ 41 , 42 ]. The NIH Early Career Reviewer (ECR) program is another attractive option, allowing junior faculty to serve on NIH review panels with a reduced workload [ 43 ]. Junior faculty in the ECR program provide valuable service to the scientific community while also learning about grantsmanship and the inner workings of the review process, and networking with other panelists in the same field. Sometimes, gaining experience as a grant reviewer can be as simple as e-mailing the scientific review officer in charge of a relevant panel at NIH, NSF or another agency to volunteer your expertise on an ad hoc basis. Of course, learning grantsmanship or another professional skill by performing service is a valuable but time-consuming activity, and you’ll want to be sure that the cost-benefit analysis is in your favor before you agree. Beyond these approaches, junior faculty can also improve their skills through advice and mentoring by senior colleagues, through formal mentoring committees or individual conversations to discuss professional challenges and strategies. During the tenure preparation marathon, it pays to explore all of these avenues to hone your skills.

Scientific recognition and networking

For a successful tenure review, your accomplishments must be appreciated by colleagues at your home institutions and beyond. We might all hope that “the research can speak for itself,” but the reality is that tenure (and all science) depends on doing high-quality work and ensuring that others know about it. Within your department, be sure that your colleagues understand and appreciate your research. If it’s highly interdisciplinary, in a brand-new field, or somehow different from most of the science in your unit, you may need to take extra care to educate your coworkers about its significance and value. Internal work-in-progress seminars on your campus and posters at department retreats (presented by you and/or your trainees) are a simple and collegial way to spread the word about your exciting projects. Outside your institution, seminars at other universities and talks at conferences are key ways of introducing yourself and your science to the community. It can be shrewd to pick one or two important conferences in your research area and attend them every year, presenting your work as often as possible, to raise awareness of your research and become a fixture in the professional network of the field. It’s also a good idea to build an attractive and informative lab web site, with your publications and research interests clearly listed. Many faculty also use social media, such as Twitter, as a tool to gather information (e.g., from journals, funding agencies and other scientists) and to advertise the accomplishments of themselves and their trainees, such as new pre-prints and papers, awards and grants. Consider applying for awards to recognize your achievements in research, teaching or service, or ask senior colleagues to nominate you when needed. A long list of awards is not typically a prerequisite for tenure, but some recognition beyond your institution doesn’t hurt.

Networking can be a tremendous help to junior faculty, by recruiting trainees, finding collaborators, meeting future grant or promotion evaluators, seeking help, raising awareness about your own accomplishments, and more. Networking may not come naturally to all scientists (or to everyone in any field), but it’s wise to learn to do it in a way that’s proactive and intentional, while remaining authentic to your own personality and style. You can begin at home, in your own department. Simple things like lingering for pizza after a seminar or joining a department happy hour or retreat to chat with colleagues and students can build collegiality and spark interesting scientific discussions. (To be clear, drinking is optional in all cases – networking at happy hour works just fine over a cup of coffee or glass of water!) Similar opportunities exist at conferences, when you visit other campuses for seminars, or when outside speakers visit you. As noted, it can be helpful to invite seminar speakers to your home institution who are likely to review your future manuscripts or grants, or write external letters for your tenure dossier (e.g., members of the NIH study section where your application will go). This strategy promotes your networking, by helping you establish good relationships with more senior scientists, and also aligns well with your research interests, because someone serving on a panel that would review your grants is likely to have similar scientific interests to your own, making them a natural choice for an interesting seminar speaker.

Conclusions

Last but certainly not least, be sure to practice self-care and remain healthy and happy as you work towards tenure. To be sure, this can be a challenge. As McGlothlin notes about new faculty positions:

For most people, this will … be their first experience leading a team. It will be the first time that there is no adviser to consult when there is a tough decision to make, which can be daunting at first. Unless you’re lucky enough to find students or postdocs right away, when you start you will be leading a team of one. This can be a huge adjustment for people used to being part of a large lab, as I had been as a grad student and a postdoc. The first year, when you’re working solo in your office or in an empty lab, can be incredibly isolating [ 26 ].

It’s important to know that this is a very common feeling – it’s not just you! – and there are concrete things you can do when fear, doubt, impostor feelings or loneliness strikes. For starters, as Robert Bloch advises, “Don’t toil away in isolation” [ 44 ]. New faculty may hesitate to ask for help, worrying that it could make them look bad. On the contrary, seeking help when you need it is a sign of maturity, wisdom and proactive good management. Your department chair is often a good first stop. Chairs and other supervisors have usually invested a lot of time and resources in you as a new faculty member, and they genuinely want you to succeed. Get their advice and assistance when you need it (while remaining respectful of their time). It’s also helpful to cultivate good relationships with both senior colleagues in your department and/or field, and other junior faculty at your institution, so you can lean on them as sources of support and offer help in return when they ask. The most supportive and valuable colleagues are often those who take a sincere interest in your work and career, whether or not their science is closely aligned with yours, and give you their honest opinions, even when it’s tough love. Online communities, such as those offered by scientific societies or groups like New PI Slack, can also be excellent wellsprings of advice and moral support [ 45 , 46 ]. And, of course, you’ll make mistakes along the way, as we all do. No one enjoys errors, but try to consider them as an inevitable part of the learning process and a sign of professional growth – however painful – and then move on. As Bloch advises new faculty, “Don’t fret about a decision once you’ve made it. You can usually correct a problem later, if you have to” [ 44 ].

Perhaps most importantly, try always to maintain a healthy work-life integration, however that is best defined for you. A tenure-track faculty position is an exciting and sometimes stressful career, but it’s only one element of life, and it has to be compatible with your physical and mental wellness, values, family and friends, religion or spirituality, and any other aspects of a fulfilling existence that matter to you. With some careful planning and help along the way, you can have a smooth arc towards tenure and beyond, while also keeping your balance in these other important realms of life.

Availability of data and materials

Not applicable.

Abbreviations

Accomplishing Career Transitions

Appointment, promotion and tenure

American Society for Cell Biology

Diversity, equity and inclusion

Department of Defense

Early Career Reviewer

National Institutes of Health

National Science Foundation

Persons excluded because of their ethnicity or race

Principal investigator

Research-intensive institution

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Acknowledgements

This article emerged from an event at the 2019 summer workshop of ASCB’s Achieving Career Transitions (ACT) program. We thank Hashim Al-Hashimi, Bob Goldstein, Patrick Martin, Christine Richardson and Verónica Segarra for helpful advice.

About this supplement

This article has been published as part of BMC Proceedings, Volume 15, Supplement 2, 2021: Accomplishing Career Transitions 2019: Professional Development for Postdocs and Tenure-track Junior Faculty in the Biomedical Sciences. The full contents of the supplement are available at https://bmcproceedings.biomedcentral.com/articles/supplements/volume-15-supplement-2 .

The ACT program (see Acknowledgements, above) and the processing charge for this article are supported by an Innovative Programs to Enhance Research Training grant from the National Institute of General Medical Sciences awarded to ASCB (2R25GM116707).

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How long does it take to get tenure, published by steve tippins on march 1, 2019 march 1, 2019.

Last Updated on: 2nd February 2024, 05:39 am

How long does it take to get tenure? Traditionally, this question is answered something like, “You must get tenure by your seventh year.” Most people go up for tenure in their 6th year so that tenure can be granted for their 7th year. While this is normal, there are other ways and timeframes for getting tenure. I’ll discuss the traditional–and nontraditional routes–here, and describe how I got early tenure.

Tenure Basics

Academic tenure is thought of by many as lifetime employment. True, once you get tenure it is harder for a school to terminate your employment, but the ultimate purpose of tenure is to give faculty the freedom to express unpopular opinions.

Don’t forget, tenure does not guarantee employment forever . Tenure can be taken away for egregious acts or if the school gets rid of your program or has serious financial issues. It’s important to keep this in mind as a number of colleges currently face serious financial issues. Considering how long it takes to get tenure, you’ll want to be sure you get it at the right place.

How Long does it take to Get Tenure?

Seven years: the traditional route.

Most new hires go through the traditional route to get tenure. In this approach, you work hard for 6 years and then submit all of your documentation to your department tenure and promotion committee.

This committee makes a decision about your tenure and then passes it on to the school promotion and tenure committee. The next step is to the university promotion and tenure committee, then on to the Provost or President for final approval.

The progression just presented assumes that you get a positive review at each level. If you get a negative review, then you need to look at the faculty handbook to determine how to proceed.  In most cases, you will be able to add additional information to your file to counter any negative reviews.

The best thing that you can do to prepare for this is to make sure that you are fully aware of all tenure requirements and sections of the faculty handbook. This way that you can anticipate most issues before they arise. Considering how long it takes to get tenure, you want to make your application as strong as possible in the beginning.

Tenure Upon Hiring

The easiest way to get tenure is to negotiate it when you are coming in the door. This rarely happens for someone just starting and applying for an Assistant Professor job . However, if you already have tenure and are looking at a job at a new school, by all means, ask for tenure as part of the package.

Your material will still be looked at by the school’s promotion and tenure committee but in my experience, once an offer has been made to you, making tenure part of the package is rarely an issue.

I have also seen administrators negotiate for tenure as part of an offer. So if you are offered a position as Dean or Provost it is common to ask for tenure along with a faculty position that you can fall back to if you are no longer in the administrative role.

Getting Early Tenure

How long it takes to get tenure isn’t set in stone. As stated earlier, most schools require that you apply for tenure before your seventh year. Just because most people wait until their seventh year doesn’t mean that you have to wait until then.

The first time I applied for tenure, I did so because I was applying for a promotion to Associate Professor (I wanted the raise as part of my base) and it was the same application and the same written criteria. I had only been at the school for four years, but the faculty handbook did not list time as a requirement for tenure.

Interestingly I was initially granted the promotion but denied tenure. Remember, same application, same criteria.

I was told informally that I had not been there long enough. Being a contrarian, I appealed the decision as the criteria were the same. Nowhere in the application or the faculty handbook was time listed as a requirement. I submitted my paperwork and was ultimately given tenure as well.

How Long Does It Take to Get Tenure? Summary

Tenure is something that most faculty members strive for . There are several paths to tenure and if you navigate them successfully, they all end with the option of long term employment. No matter which path you choose to follow, being familiar with the requirements will allow you to present the strongest application possible. Good luck!

If you’re interested in pursuing tenure, my academic career coaching program can help you do just that.

Steve Tippins

Steve Tippins, PhD, has thrived in academia for over thirty years. He continues to love teaching in addition to coaching recent PhD graduates as well as students writing their dissertations. Learn more about his dissertation coaching and career coaching services. Book a Free Consultation with Steve Tippins

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Effective Altruism Forum EA Forum

Estimation of probabilities to get tenure track in academia: baseline and publications during the phd., key takeaways:.

This article aims to estimate the probabilities of any PhD student to get a permanent position (tenure track) in academia, in order to inform career decisions. The findings have been:

• Between 10% and 30% of PhD alumni get a permanent position at academia.
• Often around 70% of PhD alumni want to work in academia.
• My estimate is that conditional on wanting to get a permanent position in academia, you should have a baseline chance between 15-30% of landing a permanent job at academia

The most important factor determining whether you actually get such positions is the number of first-authored articles, although the precise numbers by field are not known in Pure Science or Technological fields. They are nevertheless available in the Biomedical and Sociology fields.

Introduction

Contributing with a career to one important cause is perhaps one of the most effective ways of having a positive impact in the world. However, since EA careers are not so well established, the few opportunities that are available tend to grab all the attention, and less conventional choices, although celebrated, are often difficult to assess and find.

For instance, I aim to contribute to the AI Safety problem. However, it is not clear what is the best way. In my case I see two main options for next steps:

• Academic research .
• Work in an "EA organisation" or opportunity such as those that often appear in the 80000 hours job board .

Some cons of working in academia due to the long time it takes, the low chances of getting tenure, and the perverse incentives to publish a lot no matter how relevant the topic is. On the other hand, working at academia gives a lot of freedom, social status and influence and the possibility of making fields of interest to Effective Altruism (including e.g. AI safety and global priorities research)  more respectable. Some other considerations might be found in CS PhD 80000 hours career profile .

However, one factor not analysed in depth in that profile is the probability of getting a tenure position. In this post we aim to get a first estimate that could inform people.

Just to inform the reader, the typical career path in academia usually involves a PhD (~3 years in Europe, 5 in the US which also includes the master), one or two postdocs of 2-3 years each (this step may be longer, up to 7-8 years), and then obtaining access to junior research fellows, which may be promoted to professorship with time. The most difficult part seems to be changing from the temporary postdoctoral positions to the permanent research fellow one.

Approximate academic career path. The lengths are only estimated based on the comments above, actual timelines vary a lot. Junior researcher is the name I give to the first permanent position.

In order to establish a baseline, the following might be useful:

• This CS PhD career outcomes survey indicates in table D4 that around 34% of people ending their PhDs in the US remain in academia, and of those 12% go straight into tenure positions - without ever doing a postdoc.
• This document from IOP shows a graphic with data of career flows. However, I do not assign great credibility since the data is quite hard to track where exactly it comes from, and additionally it reports "For physicists, that 3.5% figure [the number of people securing a permanent research position] is probably a little low. Slightly older data collected by the Institute of Physics and the US National Science Foundation suggest that the fraction of physics PhD students who obtain permanent academic jobs has historically hovered between 10 and 20%." and "Indeed, according to an August 2012 survey carried out by the American Institute of Physics (AIP), nearly half (46%) of new physics PhD students at US institutions want to work in a university."
• In the UK, 3.5 years after graduation, around 30% of PhD holders remain in academia, according to this document based on the Long DLHE survey .
• Figures 2 and 3 of this Nature article indicate that 29% of people with a PhD in biomedical sciences end up in academia. Interestingly, since research is more common in industry in the US, tenure track positions seem to be less common compared with non-US research career paths. "US scholars enter into the for-profit sector in professional job-types conducting applied research at a much higher rate than international scholars. International scholars enter the academic sector in tenure-track job-types conducting basic research at twice the rate of US scholars".
• This article from Science indicates that around 20% of the PhD holders in the job market have a tenure position, and it is slowly decreasing. In CS and Mathematics it is a bit higher, it says, 33%.
• In this article , it is said that in the US, each faculty position will have approximately 7.4 PhD students. Hence, if the number of positions does not grow over time, only 1 in 7.4 students (i.e. 13.5% of the PhD students) would be able to replace the faculty position.
• In table 10 of the UK report What do researchers do? it is said that 34% of PhD graduates work in academia, according to the L DLHE survey that we mentioned before. That survey takes place 3.5 years after graduation. Also, in table 11 it is indicated that 29% are doing research either in academia (16.7%, which is surprisingly low from the 34%, weird definitions perhaps) or industry (12.2%).
• There is a report on several central european universities showing the perspective of PhD holders. In figure 17 it is indicated that in the first two years, 60% are employed under temporal contracts, whether between 3 and 7 years, the number of permanent positions rises to 60%. Of the surveyed PhD alumni, 46% were employed in academia. Overall, 525/2299 = 22.8% of PhD alumni have attained a permanent position in academia and a number that raises to 26.8% 5-7 years after the end of the PhD. In figure 25 it is also indicated that from the research employed people, 35% hold some postdoctoral position, and another 30% a research fellow or assistant professor position.
• This research article also analises the amount of people that reach tenure positions for STEM PhD alumni. Figure 1c gives quite optimistic data, a 21% chance of tenured for the 0-5 years after PhD range, and 37% onwards.
• This graph on biology PhD students shows 15% of them get a tenured position within 6 years. However, they expect that <10% of new PhD students will get it.

The data is somewhat confusing and contradictory, probably because I am mixing non-comparable sources. In any case, other minor comments is that in Europe there seem to be higher chances (based on point 4) and that Biology seems harder than Physics and Chemistry

Percentage of PhD students who get a permanent position in academia according to each source above.

With respect to the amount of people who want to stay in academia I have found

• Some historical calculations are indicated in this newspaper article , where this other article is mentioned.
• In this other article , it is indicated that after the PhD, 80% of the graduates want to remain in academia, whereas that number drops to 60% after three years. It is also decomposed for CS in particular (80% and 73% respectively).
• This nature article has some statistics on expectations. It gives a ~70% interest in the academic career depending on the geographical zone; and indicates that Europe is the continent where people are more pessimistic about the time needed to get tenure.

Overall, my personal estimate is that I'm 90% sure that 10-30% of students get tenure, and 65% that the intervale is between 10% and 20%. Furthermore, I estimate based on the previous sources that around 70% of the PhD alumni would want to work in academia. Hence, conditional on wanting to work in academia your baseline chances should be in the 15-30% range to start with.

Update : Since I published this article, I have found this report , that decomposes probabilities by field of study in Concordia University, Canada:

The discipline with the highest percentage of tenure-track and tenured professors is business (69%) followed by social sciences (27%), humanities (22%), engineering (21%),fine arts (14%) and sciences (11%).

Update 2 : I have found a second article on 7000 US STEM graduates detailing what percentage of people progress to the next stage, indicating that overall 21% of PhD holders get tenure, and that 24% do in Computer Science.

Pipers are those who get tenure, never are those who don't stay in academia after their PhD, droppers those who drop mid way.

Inside view: the predoctoral publication statistics

Some articles that are important in this respect:

• This article analyses several factors to predict the success of a given PhD graduate. It also says: "Despite this, a relatively small percentage of individuals successfully completing a PhD ultimately achieve this goal, with only an estimated 14% of biological sciences PhD recipients having a tenure-track faculty position 5–6 years post graduation ( Stephan, 2015 ). This rate is somewhat higher for earners of chemistry (23%) or physics (21%) PhDs."
• This other article does the same for medical sciences, but has the nice feature of indicating the average rate of publications per year and number of authors.
• This article gives some explanation of different factors, including the sex, and number of publications of the PhD supervisor.
• Another article has an analysis of different factors for the field of sociology.
• Finally, there is another nice article on different average publishing rates in Norway, by fields, gender, age and position

Some conclusions from this section is that publishing and specially first-author publishing is the largest predictor of academic success. What is much harder to find is concrete numbers for particular fields.

I believe that having a more accurate estimate of what are the actual chances of landing a job at academia can help to gauge the pros and cons of this career path.

From the previous sections it is likely (65% chance in my opinion) that the probability baseline probability of landing a permanent job at academia conditional on trying is in the 15-30% range.

However, there is a lack of data on how exactly to use the inside view to gauge personal probabilities. In particular, most studies analysing this have been done for particular fields which may not replicate in others. However, the best estimate seems to be that if you are going this path, the main metric you should be looking at is the number of articles where you are the first author. More research is needed to calibrate estimates based on inside-view factors.

I would like to thank the incredible help of Jaime Sevilla, who provided useful feedback on a draft of this article.

More posts like this

Academic here:

• Essentially all of these numbers vary wildly  across subfields, across countries, and on other assumptions like how prestigious the labs are that you're considering. Judging based on numbers from physics, or from US PhDs overall, could leave you off by an order of magnitude or more. They also vary significantly over time. 
• The populations in PhD programs vary a lot from field to field as well, and how you fit relative to those populations will help tilt the odds. Being intrinsically motivated and a good English writer (the two things I can tell about the OP) could give you a pretty big leg up in your odds of finishing and getting a job relative to the median CS PhD student at a good US research university, at least assuming that you have the technical qualifications to be admitted. In a Philosophy program, by contrast, that'd be baked into the admissions criteria, and wouldn't tell me much.
• P(admission to a good PhD program | serious effort at applying) =   1-15% without substantial prior research experience,   5-60% with limited research experience (at least one serious paper with a recognized collaborator, but nothing presented as a first author at a competitive venue)  50-90% with strong research experience (at least one paper with a recognized collaborator, presented as a first author at a competitive venue).
• P(graduate within six years | enroll) = 70-95%
• P(assistant professor job at a US top-100 research university directly after PhD | graduate within six years and apply) = 5-50% P(assistant professor job at a top-100 research university  within three years after PhD | graduate within six years and apply) = 30-75% P(long-term US research job that supports publishing, academic or otherwise, within three years after PhD | graduate within six years and apply) = 85-95%
• P(granted permanent tenure within nine years of starting as an assistant professor | make a serious attempt to stay) = 85%-98%

Hey Pablo - thanks for working this up. It's nice to have some baseline estimates!

As you say, Tregellas et al. shows that the probability of tenure varies a lot with the number of first author publications. It would be interesting to know if tenure can be predicted better with other factors like one's institution or h-index - I could imagine such a model performing much better than the baseline.

Two other queries:

• I feel like we're talking about tenure, rather than tenure track?
• When you say things like "my personal estimate of the baseline probability of getting a permanent (tenured) position in academia should be with 90% probability between 10-30%" , it might be clearer to say you're 90% sure that 10-30% of students get tenure? Otherwise I don't know how to interpret this probability of a probability.

You're right Ryan, I'll modify the second complicated sentence. I am actually not sure what is the difference between tenure and tenure track, to tell the truth. However, in one of the documents above I saw that institution is not such a strong predictor (point 4), but h index seemed useful (in point 2 the h-index is discussed).

Interesting. The point 2 article by van Dijk seems decent. Figure 1B says that the impact factor of journals, volume of publications, and cites/h-index are all fairly predictive. University rank gets some independent weighting (among 38 features, as shown in their supplementary Table S1), but not much.

Looks like although the web version has gone offline, the source code of their model is still online!

I strongly agree with Ryan that success is to a relatively large degree predictable, as can be done in the PCA decomposition of point 2 above, figure 1C. I think it would be very valuable to have such a model, but the current code is only for biology (the impact factor will fail for instance for anything different). If one wanted to fit a model to predict it, it could probably use google scholar and arxiv, but the trickiest part would be to recover the position of those people (the target), which may partially be done using google scholar.

I just posted another article I found on average publication rates in Norway for different positions, ages, fields and gender.

This is helpful, thanks.

The information is probably here somewhere, but is that the probability of getting tenure given you finish your Ph.D.? I.e. Does this account for dropping out?

Somewhat tangential, but I think accounting for the chance of working on AI safety (or something comparably effective) outside of academia will help. I think this is more common in Economics (e.g. World Bank). But I guess OpenAI or similar institutions hire CS PhDs and working there possibly has a similar impact to working in academia.

I would say you basically cannot get tenure if you don't get a PhD, so dropouts are not taken into account in any of the previous statistics as far as I understood them. All this metrics are of the kind of: x% of PhD alumni got tenure, or similar.

I actually agree that taking into account the private sector could help, but I am much less certain about the freedom they give you to research those topics, beyond the usual suspects. That was why I was focussing on academia.

In the US, about half of people who start PhD programs get the degree. Also, a big factor that I thought I commented about here (I guess they removed comments) is that most tenure track positions at least in the US are teaching intensive, so there is not much time for research.

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• Open access
• Published: 21 September 2022

Quantifying hierarchy and dynamics in US faculty hiring and retention

• K. Hunter Wapman   ORCID: orcid.org/0000-0003-2518-841X 1 ,
• Sam Zhang   ORCID: orcid.org/0000-0002-0371-9526 2 ,
• Aaron Clauset   ORCID: orcid.org/0000-0002-3529-8746 1 , 3 , 4 &
• Daniel B. Larremore   ORCID: orcid.org/0000-0001-5273-5234 1 , 3  

Nature volume  610 ,  pages 120–127 ( 2022 ) Cite this article

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An Author Correction to this article was published on 05 July 2023

This article has been updated

Faculty hiring and retention determine the composition of the US academic workforce and directly shape educational outcomes 1 , careers 2 , the development and spread of ideas 3 and research priorities 4 , 5 . However, hiring and retention are dynamic, reflecting societal and academic priorities, generational turnover and efforts to diversify the professoriate along gender 6 , 7 , 8 , racial 9 and socioeconomic 10 lines. A comprehensive study of the structure and dynamics of the US professoriate would elucidate the effects of these efforts and the processes that shape scholarship more broadly. Here we analyse the academic employment and doctoral education of tenure-track faculty at all PhD-granting US universities over the decade 2011–2020, quantifying stark inequalities in faculty production, prestige, retention and gender. Our analyses show universal inequalities in which a small minority of universities supply a large majority of faculty across fields, exacerbated by patterns of attrition and reflecting steep hierarchies of prestige. We identify markedly higher attrition rates among faculty trained outside the United States or employed by their doctoral university. Our results indicate that gains in women’s representation over this decade result from demographic turnover and earlier changes made to hiring, and are unlikely to lead to long-term gender parity in most fields. These analyses quantify the dynamics of US faculty hiring and retention, and will support efforts to improve the organization, composition and scholarship of the US academic workforce.

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Prestige plays a central role in structuring the US professoriate. Analyses of faculty hiring networks, which map who hires whose graduates as faculty, show unambiguously in multiple fields that prestigious departments supply an outsized proportion of faculty, regardless of whether prestige is measured by an extrinsic ranking or reputation scheme 11 , 12 , 13 or derived from the structure of the faculty hiring network itself 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 . Prestigious departments also exhibit ‘social closure’ 15 by excluding those who lack prestige, facilitated by relatively stable hierarchies over time, both empirically 17 and in mathematical models of self-reinforcing network dynamics 30 , 31 .

These observations are important because of the broad impacts of prestige itself. Prestigious affiliations improve paper acceptance rates in single- versus double-anonymous review 32 ; faculty at prestigious universities have more resources and write more papers 33 , 34 , receive more citations and attention 35 , 36 , 37 and win more awards 38 , 39 ; and graduates of more prestigious universities experience greater growth in wages in the years immediately after graduating 40 . Furthermore, the vast majority of faculty are employed by departments less prestigious than those at which they were trained 27 , making prestigious departments central in the spread of ideas 3 and academic norms and culture more broadly.

Less well studied are the processes of attrition that, together with hiring, shape the data underpinning the analyses reviewed above. Evidence suggests that women in science and engineering (but not mathematics) and foreign-born faculty leave the academy in mid-career at higher rates than do men 41 and US-born 42 faculty, respectively, making clear the fact that the US professoriate is structured by more than just prestige. These processes are particularly important in light of clear evidence that the topics studied by faculty depend not only on their field of study, but also on their (intersecting) identities 43 .

However, the difficulty of assembling comprehensive data on US faculty across fields, across universities and over time has limited analyses and comparisons, leaving it unclear how much of the observed patterns and differences are universal, vary by field or are driven by current or past hiring or attrition. Less visible but just as important are the inherent limitations of focusing only on the placement of faculty within the US system, to the exclusion of US faculty trained abroad. A broad cross-disciplinary understanding of academic hierarchies and their relationship to persistent social and epistemic inequalities would inform empirically anchored policies aimed at accelerating scientific discovery or diversifying the professoriate.

Data and approach

Our analysis examines tenured or tenure-track faculty employed in the years 2011–2020 at 368 PhD-granting universities in the United States, each of whom is annotated by their doctoral university, year of doctorate, faculty rank and gender. To be included in our analysis, a professor must be a member of the tenured or tenure-track faculty at a department that appears in the majority of sampled years, which yields n  = 295,089 faculty in 10,612 departments.

This dataset resulted from cleaning and preprocessing a larger US faculty census obtained under a data use agreement with the Academic Analytics Research Center (AARC). To facilitate comparisons of faculty across areas of study, we organized departments into 107 fields (for example, Physics, Ecology) and eight domains (for example, Natural Sciences) (Extended Data Table 1 ). Field labels, provided in the AARC data, and subsequently hand-checked, are not mutually exclusive, such that 23% of faculty were assigned to multiple fields (for example, members of a Department of Physics and Astronomy were assigned to both Physics and Astronomy). For faculty associated with multiple departments, we restricted our analyses to their primary appointments only. All doctoral universities were manually annotated by country. Self-reported faculty genders were used when available, and otherwise algorithmically annotated (man or woman) on the basis of historical name–gender associations, recognizing that there are expansive identities beyond this limiting binary. These procedures resulted in gender annotations for 85% of records; faculty without name–gender annotations were not included in analyses of gender but were included in all other analyses. Comparing data collected in adjacent years, we also annotated all instances of new hiring, retention and attrition. Data preparation and annotation details can be found in Methods .

To analyse patterns of faculty hiring and exchange among US universities, we created a faculty hiring network for each of the 107 fields, eight domains and for academia as a whole ( Methods ). In such a network, each node u represents a university, and a directed edge u  →  v represents an individual with a doctorate from u who becomes a professor at v . Faculty employed at their doctoral universities, so-called self-hires, are represented as self-loops u  →  u . When aggregating field-level hiring into networks for the eight domains or for academia in toto, we take the union of the constituent fields’ edges, which avoids double-counting of faculty rostered in multiple fields. Anonymized data supporting our analyses are freely available (Data availability).

Pre-eminence of US doctorates

In general, although our data show that US academia largely requires doctoral training, the ecosystem of broad domains and specialized fields exhibits diversity in its credential requirements. Fully 92.7% of all faculty hold doctoral degrees yet only 1% lack a doctorate in Social Sciences compared with 19% in the Humanities (Fig. 1a ). Even within the Humanities there is wide variation, with only 7% of remaining faculty lacking a doctorate if one separates out the fields of Theatre (67% non-doctorates), Art History (44%), Music (30%) and English (11%) (Extended Data Fig. 1 ).

a , Degrees of n  = 295,089 US faculty by domain, and for academia overall, separated by non-doctoral degrees (solid bars), US doctorates (open bars) and non-US doctorates (hatched bars). b , Continent of doctorate for n  = 31,845 faculty with non-US doctorates by domain. Within the Europe and North America bars, darkened regions correspond to faculty from the United Kingdom and Canada, respectively. c , d , Ratios of average annual attrition risks among faculty with doctorates from Canada and the United Kingdom ( c ) ( n  = 11,156), and from all countries other than Canada, the United Kingdom and the United States ( d ) ( n  = 20,689), versus all US-trained faculty, for each field (colours), domain (grey) and academia (blue), on logarithmic axes. Circles, significantly different from 1.0, χ 2 test, Benjamini–Hochberg-corrected P  < 0.05; crosses, not significant.

Source data

This variation in credentials is paralleled by US faculty trained internationally. Overall, our analysis finds that 11% of US faculty have non-US doctorates yet only 2% of Education faculty received their doctorates internationally compared with 19% of Natural Sciences faculty (Fig. 1a ). However, internationally trained faculty primarily receive their training from a limited range of geographical areas, with 35.5% trained in the United Kingdom or Canada compared with just 5.4% from all countries in Africa and the Americas, excluding Canada (Fig. 1b ).

Our data suggest that differences in country of doctoral training are not without consequence for the dynamics of the professoriate. Using the 10 years of observations in our data, we identified instances of attrition and estimated the annual per-capita risk of attrition for faculty trained in three groups of countries: Canada and the United Kingdom, the United States, and all others. Those with doctorates from Canada and the United Kingdom ( n  = 11,156) left their faculty positions at statistically indistinguishable rates compared with US-trained faculty ( n  = 238,676) in all 107 fields and eight domains, and at slightly lower rates overall (significance level  α  = 0.05, Benjamini–Hochberg-corrected χ 2 test; Fig. 1c ). In stark contrast, those with doctorates from all other countries ( n  = 20,689) left the US tenure track at markedly higher rates overall, in all eight domains and in 39 individual fields (36%), and in no field did such faculty leave at significantly lower rates ( α  = 0.05, Benjamini–Hochberg-corrected χ 2 test; Fig. 1d ). We note that our data allow us to consider hypotheses related only to country of doctoral training, not to country of citizenship or birth, leaving open questions about foreign-born yet US-trained faculty 42 .

Universal production inequality

For faculty with US doctorates, we find that academia is characterized by universally extreme inequality in faculty production. Overall, 80% of all domestically trained faculty in our data were trained at just 20.4% of universities. Moreover, the five most common doctoral training universities—UC Berkeley, Harvard, University of Michigan, University of Wisconsin-Madison and Stanford—account for just over one in eight domestically trained faculty (13.8%; Fig. 2a and Extended Data Table 3 ). Even when disaggregated into domains of study, 80% of faculty were trained at only 19–28% of universities (Fig. 2b ).

a , Proportions of US faculty produced by US universities, sorted by production rank, with the university producing the most faculty having a rank of 1 ( n  = 238,676 faculty; n  = 387 universities). Quintiles of production are highlighted with alternating colours and annotated with the number of universities falling within each. By production, the first quintile contains only eight universities and the bottom contains 308. b , Lorenz curves for faculty production at the field level (coloured lines) and at the domain level (grey lines). A point is placed at the site along the domain-level Lorenz curve where 80% of faculty have been produced.

Our analysis shows that universities that employ more faculty generally also place more of their graduates as faculty elsewhere (Pearson ρ  = 0.76, two-sided z -test P   <  10 −5 ). Nevertheless, at the level of domains and fields, faculty size alone cannot explain faculty production and placement: in academia as a whole, in all eight domains and in 91 of 107 fields (85%), faculty size and production are from significantly different distributions (Kolmogorov–Smirnov (K-S) test, Benjamini–Hochberg-corrected P   <  10 −5 for academia and domains, P   <  0.01 for fields), reproducing the findings of a previous analysis of faculty hiring networks in Business, Computer Science and History 27 . For the remaining 16 fields (15%), the hiring of one’s own graduates plays a key role: when self-hires are excluded, the distributions of hiring and production of only 12 fields (11%) remain statistically indistinguishable. In other words, inequalities in university or department size do not explain inequalities in faculty production.

The Gini coefficient is a standard way to quantify inequality in a distribution, with G  = 0 representing perfect equality and G  = 1 maximal inequality. We find that inequality in faculty production across academia as a whole is both marked ( G  = 0.75) and greater than the inequalities in seven of eight domains. Of those domains, inequality is lowest in Education ( G  = 0.67) and Medicine and Health ( G  = 0.67) and highest in the Humanities ( G  = 0.77). Similarly, inequality in faculty production at the domain level is nearly always greater than production inequality among a domain’s constituent fields. For instance, whereas G  = 0.73 for Engineering as a whole, Gini coefficients for the ten fields within Engineering range from 0.58 to 0.68 and, overall, G domain  >  G field for 104 of 107 fields (97%; Fig. 3a ). Generally, field-level faculty production distributions are heavy tailed and the universities comprising those tails are similar across fields within a given domain and, more broadly, across domains. That is, measurements of inequality in domestic faculty production increase as aggregation or scale expands, because of university-level correlation in faculty production across related fields and domains.

a , Line segments contrast the faculty production Gini coefficients calculated for newly hired faculty (filled circles; n  = 54,100) and for existing faculty (open circles; n  = 184,576) for each of the 107 fields (colours), eight domains (grey) and academia as a whole (blue). Line segments are grouped and coloured by domain. b , Annual Gini coefficients for academia and for each domain showing strong interyear consistency. c , Attrition risk as a function of university production rank by domain and for academia overall, via logistic regression, showing that university production rank is a significant predictor of annual attrition risk (two-sided t -test, Benjamini–Hochberg-corrected P  < 0.05) such that faculty trained at high-producing universities leave academia at substantially lower rates than those trained at less productive universities. The empirical average annual attrition rates vary around the fitted curves.

Faculty production inequalities are rooted in hiring but are exacerbated by attrition. Computing the domestic production Gini coefficients separately for newly hired faculty and their sitting colleagues across our longitudinal data frame, we find uniformly larger inequalities for existing faculty in every field, every domain and in academia overall (Fig. 3a ). However, cross-sectional Gini coefficients, computed separately for each year of observation, are stable over time, a pattern that rules out a simple cohort effect that would over time draw the Gini coefficients downward towards those of the newly hired faculty (Fig. 3b ). Combined, these observations suggest that distributions of faculty production change after hiring in a manner that increases observed inequalities. We tested this hypothesis directly by modelling annual attrition risk as a function of faculty production rank. For academia as a whole, all eight domains and 49 of 107 fields (46%), we find substantially higher rates of attrition among faculty trained at those universities that already produce fewer faculty in the first place (logistic regressions, two-sided t -test, Benjamini–Hochberg-corrected P   <  0.05). Put differently, most US-trained faculty come from a small number of universities and those who do not are nearly twice as likely to leave the professoriate on an annual basis (Fig. 3c ).

Women on the tenure track

In addition to inequalities in production, our analysis expands on well-documented gender inequalities 8 . Whereas the majority of tenure-track US faculty in our data are men (64%), we find substantial heterogeneity by area of study with moderate change over time. For instance, between 2011 and 2020, women’s representation rose from 12.5 to 17.1% among faculty in Engineering and from 55.4 to 58.5% among faculty in Education (Fig. 4a ). In fact, women’s representation significantly increased in academia overall, in all eight domains and in 80 (75%) of 107 fields (one-sided z -test, Benjamini–Hochberg-corrected P   <  0.05; Fig. 4a ). Nursing, a majority-women field, is the single instance in which the representation of women significantly decreased. The representation of women among faculty is thus generally increasing, even as women remain broadly under-represented.

a , Representation of women over time, coloured by domain and academia ( n  = 162,408 men, n  = 89,429 women). b , Line segments contrast percentages of women among newly hired faculty (filled circles; n  = 59,007) and women among all-cause attritions (open circles; n  = 90,978) for each of the 107 fields (colours), eight domains (grey) and academia as a whole (blue). Line segments are grouped and coloured by domain. c , Representation of women by career age, quantified by years since doctorate, coloured by domain and for academia as a whole. Lines indicate empirical proportions, bands indicate 95% confidence intervals.

Changes in the overall representation of women over time could be driven by many factors, including demographic changes in new hires between 2011 and 2020 or simply demographic turnover—differences between those entering and those retiring or leaving the professoriate before retirement. Investigating these potential explanations we first found that, between 2011 and 2020, the proportion of women among newly hired faculty did not change significantly in 100 of 107 fields (93%) and significantly decreased in the remaining seven fields (7%). However, by comparing the inflows of new hires with the outflows of departing faculty over our decade of observation we found that, in academia, all eight domains, and 103 of 107 fields (96%),  newly hired faculty were substantially more likely to be women than their departing counterparts (Fig. 4b ). This pattern in all-cause attrition is driven by dramatic demographic turnover, with retirement-age faculty skewing heavily towards men (Fig. 4c ), implying that the overall increases in women’s representation over this period of time (Fig. 4a ) are primarily due to changes in faculty hiring that predate our decade of observation. Importantly, the fact that women’s representation among new hires has remained flat over the past decade, combined with the observation that newly hired faculty are still more likely to be men (in academia, six of eight domains (75%) and 75 of 107 fields (70%); Fig. 4b ), suggests strongly that future gender parity in academia—and especially in Science, Technology, Engineering and Mathematics (STEM) fields—is unlikely without further changes in women’s representation among new faculty.

Self-hiring

Professors who are employed by their doctoral university, called self-hires, account for roughly one in 11 (9.1%) of all US professors in our data (11% of US-trained professors). Whereas these rates remain generally low compared with other countries (for example, 36% in Russia 44 , 67% in South Africa 29 and 73% in Portugal 45 ), they are nevertheless consistently greater than would be expected under a network-based null model that randomizes hiring patterns while keeping faculty production (outflow) and faculty hiring (inflow) fixed 46 . Self-hiring rates were similarly higher than expected across individual fields, ranging from 1.1-fold higher in Theatre to 29.3-fold in Nursing. Self-hiring rates also vary considerably by domain, being lowest in the Humanities (4.5%) and Social Sciences (6.0%) and highest in Medicine and Health (16.7%; Fig. 5a ).

a , Self-hiring rates overall (open bars; n  = 295,089), for women (solid; n  = 89,429) and for men (hatched; n  = 162,408), by domain and across academia. Dots overlaid on open bars indicate the expected rate of self-hiring under the network-based null model. b , Ratios of average annual attrition risks among self-hires ( n  = 26,720) versus all other faculty ( n  = 268,369) for each field (colours), domain (grey) and academia (blue), on logarithmic axes. Circles, significantly different from 1.0, χ 2 test, Benjamini–Hochberg-corrected P   <  0.05; crosses, not significant.

Previous work found that women were self-hired at higher rates than men in Computer Science 47 . We find overall that 11.2% of women are self-hires compared with 8.2% of men (two-sided z -test for proportions, Benjamini–Hochberg-corrected P  < 10 −5 ; Fig. 5a ). However, this effect is driven by a minority of fields: only 26 (24%) showed differences in self-hiring rates by gender (two-sided z -test for proportions, Benjamini–Hochberg-corrected P  < 0.01), 25 of which featured more frequent self-hiring among women than men. These differences are particularly common in Medicine and Health, where in 12 of 18 fields women are self-hired at significantly higher rates than men.

We also find that self-hires are at greater risk of attrition than non-self-hires. In academia, self-hires in our data leave at 1.2-fold the rate of other faculty and rates are similarly elevated in all eight domains, as well as in 36 of 107 fields (34%; two-sided z -test for proportions, Benjamini–Hochberg-corrected P  < 10 −5 for academia, P  < 0.05 for fields and domains; Fig. 5b ). Relative rates of self-hire attrition are highest in Criminal Justice and Criminology and Industrial Engineering, at 1.9- and 1.8-fold the rate of other faculty, respectively. Only in Nursing was the relative rate of self-hire attrition significantly below 1.0 (0.9-fold). It is unclear what drives these differences but, given the ubiquity of self-hired faculty and differential rates of attrition, determining and addressing the causes of this phenomenon would have a wide impact.

Ubiquitous hierarchies of prestige

If a faculty hiring market were to follow a strict social hierarchy, no university would hire a graduate from a university less prestigious than its own—100% of faculty would hold positions of equal or lower prestige than their doctoral training. The extent to which empirical faculty hiring networks follow perfect hierarchies has direct implications for academic careers, the mobility of the professoriate and the flow of scientific ideas 3 , 37 . Treating the flows of faculty between US universities as a network leads to a natural, recursive definition of prestige: a department is prestigious if its graduates are hired by other prestigious departments. We apply the SpringRank algorithm 48 to each faculty hiring network to find, in approximation, an ordering of the nodes (universities) in that network that best aligns with a perfect hierarchy; this ordering represents the inferred hierarchy of prestige.

Faculty hiring networks in the United States exhibit a steep hierarchy in academia and across all domains and fields, with only 5–23% of faculty employed at universities more prestigious than their doctoral university (Fig. 6a,b and Extended Data Table 4 ). Measured by the extent to which they restrict such upward mobility, these prestige hierarchies are most steep in the Humanities (12% upward mobility) and Mathematics and Computing (13%) and least steep in Medicine and Health (21%; Fig. 6b ). We tested whether these steep hierarchies could be a natural consequence of inequalities in faculty production and department size across universities, using a null model in which we randomly rewired the observed hiring networks while preserving out-degree (placements) and in-degree (hires) and ignoring self-loops (self-hires) 46 . For each rewired network we re-ranked nodes using SpringRank and measured induced upward mobility as a test statistic (fraction of up-hierarchy edges; Methods ). For academia as a whole, all domains and 94 of 107 fields (88%), empirical networks showed significantly steeper prestige hierarchies than their randomized counterparts (one-sided Benjamini–Hochberg-corrected P   <  0.05; Fig. 6c and Extended Data Table 5 ). No field was significantly less steep, although networks in the fields of Pharmacy ( P  = 0.88), Immunology ( P  = 0.77) and Pathology ( P  = 0.73) were less steep than null model randomizations most frequently. In short, the prestige hierarchies that broadly define faculty hiring are universally steep, and often substantially steeper than can be explained by the ubiquitous and large production inequalities.

a , Prestige change from doctorate to faculty job in the US faculty hiring network ( n  = 238,281; Methods ), with ranks normalized to the unit interval and 1.0 being the most prestigious. The proportions of faculty at universities less prestigious than their doctorate are annotated as 'move down' (open bars), at universities more prestigious than their doctorates as 'move up' (hatched) and at the same university as self-hires (solid). b , Rank change among faculty in the US faculty hiring network, by domain, using the same shading scheme as in Fig. 1a . c , Comparison between empirical hierarchies and those from 1,000 draws from a null model of randomly rewired hiring networks ( Methods ), quantified through upward mobility. Fields above the diagonal reference line exhibit steeper hierarchies than can be explained by department size and faculty production inequalities alone. Circles, Benjamini–Hochberg-corrected P  < 0.05, network null model ( Methods ); crosses, not significant; no field was significantly less steep than expected. d , Heatmap of pairwise Pearson correlations between prestige hierarchies of fields.

Inferred prestige ranks of universities are also highly correlated across fields, suggesting that many factors that drive field-level prestige operate at the university level. Among pairwise correlations of university prestige rankings across fields, the overwhelming majority are positive (all but 116 of 12,024) and nearly half (48%) have a correlation >0.7 (Pearson’s ρ ). Fields in Engineering, Mathematics and Computing, and Humanities are particularly mutually correlated whereas the field of Pathology is, on average, the least correlated with others (mean correlation 0.2).

Patterns across field-level 'top-10' most prestigious departments illustrate other aspects of the stark inequalities that define US faculty hiring networks. Among the 1,070 departments that are ranked top-10 in any field, 248 (23.2%) top-10 slots are occupied by departments at just five universities—UC Berkeley, Harvard, Stanford, University of Wisconsin-Madison and Columbia; fully 252 universities (64%) have zero top-10 departments. These findings show that, both within individual fields and across entire domains, faculty placement power is highly concentrated among a small set of universities, complementing the already enormous concentration of faculty production among the same set of universities (Fig. 2 ). Together, these patterns create network structures characterized by a closely connected core of high-prestige universities that exchange faculty with each other and export faculty to—but rarely import them from—universities in the network periphery (Extended Data Fig. 2 ).

As a result of both systematic inequality in production and steep social hierarchies, the typical professor is employed at a university that is 18% further down the prestige hierarchy than their doctoral training (Fig. 6a , Extended Data Table 6 ). Combined with sharply unequal faculty production (Fig. 2 ), this movement downward in prestige implies that the typical US-trained professor can expect to supervise 2.4-fold fewer future faculty than did their doctoral advisor. At the field level, the typical professor who moves downward descends by between 28% (Electrical Engineering) and 46% (Classics) of the prestige hierarchy whereas the typical professor who moves upward, of whom there are very few, ascends by between 6% (Economics) and 26% (Agronomy) of the hierarchy. There was no significant difference in mobility between men and women in 82 of 107 fields, but of the 25 fields in which mobility did differ by gender (two-sided z -test for proportions, Benjamini–Hochberg-corrected P   <  0.05), women were less likely to move down the prestige hierarchy and more likely to be self-hires (Extended Data Table 6 ); 11 of those 25 fields were within the domain of Medicine and Health. However, we found no significant differences in the magnitudes of upward or downward movements between men and women for all fields (K-S test, Benjamini–Hochberg-corrected α  = 0.05).

Prestige helps explain more than just the flows of faculty between US universities. For instance, across all domains, our analysis shows that sitting faculty are markedly more likely to be self-hires as prestige increases, yet this relationship is progressively weaker among younger faculty cohorts (Extended Data Fig. 3 ) and is either attenuated or not significant for new hires (two-sided t -test, Benjamini–Hochberg-corrected α  = 0.05; Extended Data Fig. 4a ). By contrast, new hires in all domains are substantially more likely to be trained outside the United States as prestige increases, yet this relationship is either attenuated, not significant or even reversed for sitting faculty (two-sided t -test, Benjamini–Hochberg-corrected α  = 0.05; Extended Data Fig. 4b ). Although we observe no common relationship across domains between prestige and gender, both new and existing faculty are more likely to be men as prestige increases for academia as a whole (two-sided t -test, Benjamini–Hochberg-corrected P   <  0.05; Extended Data Fig. 4c ). Together, these observations suggest complicated interactions between prestige and the processes of hiring or retaining women, one’s own graduates and graduates from abroad, patterns that complement previously observed effects of prestige on peer review outcomes 49 , 50 and productivity 34 .

As a whole, by domain and by field, US tenure-track faculty hiring is dominated by a small minority of US universities that train a large majority of all faculty and sit atop steep hierarchies of prestige. Just five US universities train more US faculty than all non-US universities combined. As we expand our view from fields to entire domains, inequalities in faculty production further increase, reflecting elite universities’ positions at or near the top of multiple correlated prestige hierarchies across fields. In principle, universities are on equal footing as both producers and consumers in the faculty hiring market. However, the observed patterns of faculty hiring indicate that the system is better described as having a universal core–periphery structure, with modest faculty exchange among core universities, substantial faculty export from core to periphery and little importation in the reverse direction or from outside the United States.

Although significant efforts have been made over many years to make faculty hiring practices more inclusive, our analysis suggests that many inequalities at the faculty hiring stage are later magnified by differential rates of attrition. For instance, our analysis showed higher rates of attrition among US faculty who were (1) trained outside the United States, Canada or the United Kingdom, (2) trained at universities that have produced relatively fewer faculty overall and (3) employed at their doctoral alma mater. Combined with our observations of unchanging proportions of these groups over time, these differential attrition rates suggest a dynamic equilibrium of countervailing patterns of hiring and attrition. Identifying the causes of these elevated attrition rates is likely to provide insights and opportunities to improve retention strategies for faculty of all kinds.

Our analyses of the hiring and retention of women faculty point to stalled progress towards equal representation. Whereas women’s overall representation has increased steadily across all eight broad domains of study, women nevertheless remain under-represented among new hires in many fields, particularly in STEM, and women’s representation among newly hired faculty over the past decade has generally been flat. As a result, the continued increase in women’s overall representation can instead be attributed to the disproportionate number of men among retiring faculty, across all domains. Continued increases in women’s representation among faculty are therefore unlikely if the past decade’s pattern remains stable.

Around one in 11 US professors are employed by their doctoral university. Such high rates of self-hiring across fields and universities are surprising, because academic norms treat self-hiring negatively—for example, it is sometimes called 'academic inbreeding' 51 . Elevated self-hiring rates may indicate an unhealthy academic system 52 because self-hiring restricts the spread of ideas and expertise 3 , and many decades of study suggest that it can correlate with lower quantity and quality of scholarship 53 , 54 . In this light, the sharply elevated rates of self-hiring at elite universities present a puzzle 51 , with uncertain epistemological consequences, yet these trends seem to be driven less by recent new hires and more by attrition or hiring patterns preceding our decade of observation. Overall, high rates of self-hiring persist in spite of (not because of) differential rates of attrition, with self-hires leaving US academia at higher rates in most fields, all domains and academia overall.

Our analyses describe system-wide patterns and trends, and hence say little about individual faculty experiences or the causal factors that predict the outcomes of individual faculty placements in the US academic system 55 . At best, our results provide statistical estimates for the direction and distance of faculty placements up or down a field’s prestige hierarchy, and they should not be used to inform or shape expectations of real hiring decisions. In other words, even though there are clear and strong patterns at the system level, the considerable variance in outcomes at the individual level shows that pedigree is not destiny.

One limitation of the present work is that, although doctoral universities were known, doctoral departments were not. Hence, our estimates of self-hiring rates reflect faculty employed by any department at their doctoral university, but not necessarily by their doctoral department. Our analyses therefore estimate only upper bounds on department-level self-hiring. Similarly, our estimates of production and prestige inequalities in individual fields reflect the volume and power of universities placing faculty into those fields, but not necessarily the volume of graduates produced by those fields or the related fields into which they may be hired 26 .

Our data also lack self-identified demographic characteristics and national origin, which limits the conclusions we may draw about the interaction between faculty hiring and representation by race, gender, socioeconomic background and nationality, and any intersectional analyses thereof. For instance, whereas we observe that faculty trained outside the United States constitute 2–19% of US faculty across domains, the fraction of US faculty born outside the United States is considerably higher 42 . Given our identification of markedly higher attrition rates for faculty trained outside the United States, Canada and the United Kingdom, an investigation of attrition by national origin could help identify its causes and address its differential impacts. Our approach also relies on cultural associations between name and binary man–woman genders, leaving the study of self-identified and more expansive identities, as well as intersectional representation more broadly, as open lines of enquiry.

Although our analysis shows that the clear cross-sectional patterns in faculty demographics and hiring networks are shaped by complex and evolving patterns of hiring and attrition alike, our analysis does not causally identify the mechanisms responsible. Our observations of clustered patterns among fields within the same domain suggest a role for domain-level macrocultures 56 . Strong correlations between a university’s ranks across different fields may indicate status signalling 57 , the impacts of elite universities’ resources on individuals’ productivity and prominence 34 , or other factors entirely. And, clear cohort effects—particularly in the representation of women—show non-stationarity in the patterns we observe and in the latent factors that drive them. Critically, future progress in understanding the causal factors shaping the US professoriate must investigate the factors that drive differential attrition, including those related to social identity, doctoral training (both abroad and domestically) and university of employment. Understanding the underlying causes of these differential attrition rates would surely inform efforts and policies aimed at mitigating social inequalities by improving equity and representation, which is likely to shape what discoveries are made and who makes them.

Data preparation overview

The data used in our analyses are based on a census of the US academic market obtained under a data use agreement with AARC. That unprocessed dataset consisted of the employment records of all tenured or tenure-track faculty at all 392 doctoral-degree-granting universities in the United States for each year between 2011 and 2020, as well as records of those faculty members’ most advanced degree. We cleaned, annotated and preprocessed that unprocessed dataset to ensure consistency and robustness of our measurements, resulting in the data used in our analyses.

Cleaning the original dataset involved nine steps, which were performed sequentially. After cleaning, we augmented the processed dataset with two pieces of extra information to enable further analyses of faculty and universities, by annotating the country of each university and the gender of each professor. The nine preparation steps and two annotation steps are described below.

Data preparation steps

The first step in preparing the dataset was to de-duplicate degree-granting universities. These universities are in our data either because they were 'employing' universities covered by the AARC sample frame (all tenure-track faculty of US PhD-granting universities) or because they were 'producing' universities at which one or more faculty members in the AARC sample frame obtained their terminal degree (university, degree, year). Producing universities include those based outside the United States and those that do not grant PhDs. Thus, due to the AARC sample frame, all employing universities are US-based and PhD granting, and this set of 392 universities did not require preprocessing. On the other hand, producing universities—those where one or more employed faculty earned a degree—may or may not be PhD granting and may or may not be located in the United States.

Producing universities were cleaned by hand: instances in which single universities were represented in multiple ways ('University of Oxford' and 'Keble College', for example) were de-duplicated and, in the rare instances in which a degree referenced an unidentifiable university ('Medical University, England', for example), the degrees associated with that 'university' were removed but the individuals holding those degrees were not removed.

The second step in preparing the dataset was to clean faculty members' degrees. Terminal degrees are recorded for 98.2% of faculty in the unprocessed data: 5.7% of these degrees are not doctorates (5.3% are Master’s degrees and 0.4% are Bachelor’s degrees). We treated all doctoral degrees as equivalent—for example, we drew no distinction between a PhD and a D.Phil. We note that faculty without doctorates are distributed unevenly throughout academia, with members in the Humanities and Applied Sciences being least likely to have a doctoral degree (Extended Data Fig. 1 ).

Faculty without doctorates were included in analyses of gender. They were also included in the denominators of self-hiring rate calculations but, possessing no doctorates, they were never considered as potentially self-hires, themselves. Faculty without a doctorate were not included in analyses of production and prestige, which were restricted to faculty with doctorates.

The third step in preparing the dataset was to identify and de-duplicate departments. We ensured that no department was represented multiple different ways, by collapsing records due to (1) multiple representations of the same name (for example, 'Computer Science Department' versus 'Department of Computer Science') and (2) departmental renaming (for example, 'USC School of Engineering' versus 'USC Viterbi School of Engineering'). Although rare instances of the dissolution or creation of departments were observed, we restricted analyses that did not consider time to those departments for which data were available for a majority of years between 2011 and 2020, and restricted longitudinal analyses to only those departments for which data were available for all years.

The fourth step in preparing the dataset was to annotate each department according to a two-level taxonomy based on the field (fine scale) and domain (coarse scale) of its focus. This taxonomy allowed us to analyse faculty hiring at both levels, and to compare patterns between levels. Extended Data Table 1 contains a complete list of fields and domains.

Most departments received just one annotation, but some received multiple annotations due to their interdisciplinarity. This choice was intentional, because the composition of faculty in a 'Department of Physics and Astronomy' is relevant to questions focused on the composition of both ('Physics, Natural Sciences') and ('Astronomy, Natural Sciences'). On the basis of this premise, we include both (or all) appropriate annotations for departments. For instance, the above hypothetical department and its faculty would be included in both Physics and Astronomy analyses. The basic unit of data in our analyses is therefore the individual–discipline pair. A focus on the individual would be preferable, but would require taxonomy annotations of individuals rather than departments—information we do not have. Furthermore, many individuals are likely to consider themselves to be members of multiple disciplines.

Whenever a university had multiple departments within the same field, those departments were considered as one unit. To illustrate how this was done, consider the seven departments of Carnegie Mellon’s School of Computer Science. All seven departments were annotated as Computer Science and treated together in analyses of Computer Science.

Some fields have the potential to conceptually belong to multiple domains. For example, Computer Engineering could be reasonably included in the domain of either Formal Sciences (which includes Computer Science) or Engineering (which includes Electrical Engineering). Similarly, Educational Psychology could be reasonably included in the domain of Education or of Social Sciences. In these instances, we associated each such field with the domain that maximized the fraction of faculty whose doctoral university had a department in that domain. In other words, we matched fields with domains using the heuristic that fields are best associated with the domains in which their faculty are most likely to have been trained.

The fifth step in preparing the dataset was to remove inconsistent employment records. Rarely, faculty in the dataset seem to be employed at multiple universities in the same year. These cases represent situations in which a professor made a mid-career move and the university from which they moved failed to remove that professor from their public-facing records. We removed such spurious and residual records for only the conflicting years, and left the records of employment preceding such mid-career moves unaltered. This removed only 0.23% of employment records.

The sixth step in preparing the dataset was to impute missing employment records. Rarely, faculty disappear from the dataset only to later reappear in the department they left. We considered these to be spurious 'departures', and imputed employment records for the missing years using the rank held by the faculty before becoming absent from the data. Employment records were not imputed if they were associated with a department that did not have any employment records in the given year. Imputations affected 1.3% of employment records and 4.7% of faculty.

The seventh step in preparing the dataset was to exclude non-primary appointments such as professors’ associations or courtesy/emeritus appointments with multiple departments. We identified primary appointments by making the following two assumptions. First, if a professor was observed to have just one appointment in a particular year, then that was their primary appointment for that year—as well as for any other year in which they held that appointment (including years with multiple observed appointments). This corresponds to a heuristic that faculty should appear on the roster of their primary unit before appearing on non-primary rosters. Second, if a professor was observed to have appointments in multiple units, and a promotion (for example, from Assistant Professor to Associate Professor) was observed in one unit’s roster but not in another’s, it was assumed that the non-updating unit is not a primary appointment. This corresponds to a heuristic that, if units vary in when they report promotions, it is more likely that the primary unit is updated first and thus units that update more slowly are non-primary.

Primary appointments could not be identified for 1.2% of faculty, and 5.5% of appointments were classified as non-primary. Field- and domain-level analyses were restricted to primary appointments, but analyses of academia included faculty regardless of whether their primary appointment(s) could be identified, under the assumption that employment in a tenure-track position implies having some primary appointment, identifiable or not.

The eighth step in preparing the dataset was to carefully handle employment records with mid-career moves so that each faculty member was associated with only a single employing university. Mid-career moves do not alter a professor’s doctoral university or gender, and so cannot affect measurements such as a discipline’s faculty production Gini coefficient, its gender composition or the fraction of faculty within the discipline that holds a degree from outside the United States. However, mid-career moves have the potential to alter a discipline’s self-hire rate and the steepness of its prestige hierarchy. This raises important questions for how one should treat mid-career moves when performing calculations that average over our decade of observations—should one analyse the appointment before or the appointment after the move(s)?

First we chose to use, whenever possible, the most recent employing university of each professor. In other words, if a professor was employed at multiple universities between 2011 and 2020, only that university where they were most recently employed was considered. Second, we checked that this choice did not meaningfully affect our analyses of self-hiring or prestige, because 6.9% of faculty made a mid-career move within our sample frame. To evaluate the impact of this choice on self-hiring analyses, we first calculated self-hiring rates on the basis of faculty members’ first employing university (that is, their pre-mid-career-move university if they had a mid-career move). We then calculated self-hiring rates on the basis of faculty members’ last employing university (that is, their post-mid-career-move university if they had a mid-career move). Comparing these two estimates we found that, across all 107 fields, eight domains and academia, mid-career moves had no significant effect on our measurements of self-hiring rates (two-sided z -test for proportions, α  = 0.05, n  = 295,089 faculty in both samples). To evaluate the impact of this choice on prestige hierarchies, we first calculated the upward mobility in rank-sorted faculty hiring networks on the basis of faculty members’ first employing university (that is, their pre-mid-career move university if they had a mid-career move). We then followed the same procedure but on the basis of faculty members’ last employing university (that is, their post-mid-career move university if they had a mid-career move). Comparing these two approaches, we found that mid-career moves did not significantly alter upward mobility in any field or domain (two-sample, two-sided z -test for proportions, Benjamini–Hochberg-corrected α  = 0.05; see Extended Data Table 1 for n ). At the academia level, taking the most recent university rather than the first university among mid-career moves resulted in 0.7% more upwardly mobile doctorate-to-faculty transitions (two-sample, two-sided z -test for proportions, Benjamini–Hochberg-corrected P  <  0.05, n  = 238,281 in both samples).

The ninth and final step in preparing the dataset was to exclude departments that were inconsistently sampled. Not all departments in the unprocessed dataset were recorded by the AARC in all years, for reasons outside the control of the research team. To ensure robustness of results, we restricted our analyses that did not consider time to those departments that appeared in a majority of years between 2011 and 2020. This resulted in the removal of 1.8% of employment records, 3.4% of faculty and 9.1% of departments. Additionally, 24 employing universities (6.1%) were excluded by this criterion, most of which were seminaries.

Annotations

The country of each producing university was determined by hand. First, Amazon Mechanical Turk was used to gather initial annotations. Each university was annotated by two different annotators. Inter-annotator agreement was >99% and disagreements were readily resolved by hand. To ensure no errors, a second pass was completed by the researchers and resulted in no alterations.

Self-identified gender annotations were provided for 6% of faculty in the unprocessed dataset. To annotate the remaining faculty with gender estimates, we used a two-step process based on first and last names. First, complete names were passed to two offline dictionaries: a hand-annotated list of faculty employed at Business, Computer Science and History departments (corresponding to the data used in ref. 27 ) and the open-source python package gender-guesser 58 . Both dictionaries responded with one of the following classifications: female, male or unable to classify. Second, for cases in which the dictionaries either disagreed or agreed but were unable to assign a gender to the name, we queried Ethnea 59 and used the gender to which they assigned the name (if any). Using this approach we were able to annotate 85% of faculty with man or woman labels. Faculty whose names could not be associated with a gender were excluded from analyses of gender but included in other analyses. This methodology associates names with binary (man/woman) labels because of technical limitations inherent in name-based gendering methodologies, but we recognize that gender is non-binary. The use of these binary gender labels is not intended to reinforce a gender binary.

Per-analysis inclusion criteria

The prepared and annotated dataset contained 295,089 individuals employed at 368 universities, and was used as the basis of all of our analyses. In some analyses, further inclusion criteria were applied but with the guiding principle that analyses should be as inclusive as possible and reasonable. For example, analyses of the professoriate by gender considered only faculty with a gender annotation but did not require members to hold a doctorate. Analyses of prestige, on the other hand, considered only those faculty with doctorates from US universities but did not require that faculty have a gender annotation. The aim of these inclusion criteria was to ensure the robustness of results while simultaneously being maximally inclusive. When an analysis fell into more than one of the above categories, inclusion criteria for all categories were applied. For example, when analysing changes in US faculty production over time, inclusion criteria for analyses of both US faculty production and over time were applied.

Some fields and domains were excluded from field- or domain-level analyses, either because they were too small or because they were insufficiently self-contained. Faculty in excluded fields were nevertheless included in domain- and academia-level analyses, and those in excluded domains were nevertheless included in academia-level analyses (Extended Data Table 2 ).

Two domains were excluded from domain-level analysis: (1) Public Administration and Policy and (2) Journalism, Media and Communications. These domains were excluded because they employed far fewer faculty than other domains, and because their inclusion made domain-level comparisons difficult.

Fields were included in field-level analyses only if (1) at least 25% of universities had a department in that field or (2) the number of faculty with a primary appointment in that field, and who also earned their doctorate from a university that had a department in that field, was ≥500. These requirements were intended to ensure the coherence of fields for analyses of production and prestige. For information on the number of faculty excluded from field- and domain-level analyses, see Extended Data Table 2 .

Analyses of production and prestige included only faculty who hold a US doctorate. Faculty without a doctorate are a small minority of the population in most fields, and were excluded because their degrees are not directly comparable to doctorates. Faculty with non-US doctorates were excluded because the universities that produced them are outside the sample frame.

For all longitudinal analyses, we required departments to be sampled in all years between 2011 and 2020 to ensure consistency in the sample frame. This resulted in the removal of 5.9% of employment records, 7.2% of faculty and 12.6% of departments for those analyses. Additionally, 15 employing universities (4.1%) were excluded by this criterion.

Identification of new hires

Some analyses required us to divide faculty into two complementary sets: new hires and existing faculty. For analyses that aggregated faculty over our decade of observation, we labelled faculty as new hires if they earned their degree within 4 years of their first recorded employment as faculty. Thus defined there are 59,007 new faculty, making up 20.0% of the faculty in the dataset. Our longitudinal analyses were more strict, such that faculty were labelled as new only in their first observed year of employment, but were considered as existing faculty for each observed year thereafter.

Identification of attrition and calculation of attrition risk

A professor who leaves academia for any reason constitutes an attrition, including retirement, termination of employment for any reason, acceptance of a position outside our sample frame (for example, in industry, government or a university outside the United States) or death. Our unprocessed data do not allow us to identify reasons for attrition. A professor’s last year of employment is considered the year of their attrition when counting attritions over time. Faculty who change disciplines are not considered to be attritions from disciplines they leave. Because attritions in a given year are identified through comparison with employment records in the next, attrition analyses do not include the final year of the sample frame (2020). Faculty were counted as an attrition at most once; a professor who appeared to leave multiple times was considered an attrition only on exiting for the last time.

Attrition risk is defined, for a given set of faculty in a given year, as the probability that each professor in that set failed to appear in the set in the next year—that is, the proportion of observed leaving events among possible leaving events on an annual basis. Thus, all attrition risks as stated in this study are annual per-capita risks of attrition. Average annual attrition risks were formed by counting all attrition events and dividing by the total person-years at risk.

Faculty hiring networks

Faculty hiring networks represent the directed flows of faculty from their doctoral universities to their employing universities. As such, each node in such a network represents a university and each weighted, directed edge represents the number of professors trained at one university and who are employed at the other. For the purposes of the faculty hiring networks analysed here, we restrict the set of nodes to, at most, those employing universities within the AARC sample frame. This means that nodes representing non-US universities are not included, and therefore the edges that would link them to in-sample universities are also not included. Without loss of generality, we now describe in more precise detail the creation of a particular field’s faculty hiring network, but this process applies equivalently for both domains and academia as a whole.

First, universities were included in a field only if they had a unit (for example, a department, or departments) associated with that field. As a result, a university appears in the rankings for a field only if it has a representative unit; without a Department of Botany, a university cannot be ranked in Botany. Second, ranks are identifiable from patterns in faculty hiring only if every unit employs at least one individual in that field who was trained at a unit that also employs faculty in that field. Phrased from the perspective of the faculty hiring network, this requirement amounts to ensuring that the in-degree of every node is at least one. Because the removal of one unit (based on the above requirements) might cause another to fail to meet the requirements, we applied this rule repeatedly until it was satisfied by all units.

The outcome of this network construction process is a weighted, directed multi-graph A ( k ) such that: (1) the set of nodes i  = 1,2,... represent universities with a department or unit in field k . (2) The set of edges represent hiring relationships, such that \({A}_{ij}^{(k)}\) is an integer count of the number of faculty in field k who graduated from i and are employed at j . Thus A ( k ) is a positive, integer-weighted, non-symmetric, network adjacency matrix for field k . (3) The out-degree \({d}_{i}^{(k)}={\sum }_{j}{A}_{ij}^{(k)}\) is greater than or equal to one for every node i , meaning that every university has placed at least one graduate in field k . (4) The in-degree \({d}_{j}^{(k)}={\sum }_{i}{A}_{ij}^{(k)}\) is greater than or equal to one for every node j , meaning that every university has hired at least one graduate from field k .

To infer ranks in faculty hiring networks meeting the criteria above, we used the SpringRank algorithm 48 without regularization, producing a scalar embedding of each network’s nodes. Node that embeddings were converted to ordinal rank percentiles. (In principle, embeddings may produce ties requiring a rule for tie-breaking when converting to ordinal ranks. However, no ties in SpringRanks were observed in practice).

To determine whether properties of an empirically observed hierarchy in a faculty hiring network could be ascribed to its in-degree sequence (unit sizes) and out-degree sequence (faculty production counts) alone, we generated an ensemble of n  = 1,000 networks with identical in- and out-degrees that were otherwise entirely random, using a degree-preserving null model called the configuration model 46 , 60 . We excluded self-hires (that is, self-loops) from randomization in the configuration model for a subtle but methodologically important reason. We observed that self-hires occur at much higher rates in empirical networks than expected under a configuration model. As a result, were we to treat self-hires as links to be randomized, the process of randomization would, itself, increase the number of inter-university hires from which ranks were inferred. Because of the fact that SpringRank (or an alternative algorithm) infers ranks from inter-university hires, but not self-hires, the act of 'randomizing away' self-hires would thus distort ranks, as well as the number of potential edges aligned with (or aligned against) any inferred hierarchy. In short, randomization of self-hires would, in and of itself, distort the null distribution against which we hope to compare, dashing any hope of valid inferences to be drawn from the exercise. We note, with care, that when computing the fraction of hires violating the direction of the hierarchy, either empirically or in the null model, we nevertheless included self-hires in the total number of hires—that is, the denominator of said fraction. These methodological choices follow the considerations of the configuration model 'graph spaces' introduced by Fosdick et al. 46 .

Reporting summary

Further information on research design is available in the  Nature Research Reporting Summary linked to this article.

Data availability

All network data associated with this study and all data contained in Extended Data tables are freely available in machine-readable format at https://doi.org/10.5281/zenodo.6941651 . Explorable visualizations of faculty hiring networks and university ranks are available at https://larremorelab.github.io/us-faculty/ .  Source data are provided with this paper.

Code availability

Open-source code related to this study is available at https://doi.org/10.5281/zenodo.6941612 .

Change history

05 july 2023.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-023-06379-9

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Acknowledgements

The authors thank A. Morgan, N. LaBerge and C. J. E. Metcalf for valuable feedback, and acknowledge the BioFrontiers Computing Core at the University of Colorado Boulder for providing High Performance Computing resources supported by BioFrontiers IT. This work was supported by an Air Force Office of Scientific Research Award (no. FA9550-19-10329, all authors), by a National Science Foundation Graduate Research Fellowship Award (no. DGE-2040434, S.Z.) and by a National Science Foundation Alan T. Waterman Award (no. SMA-2226343, D.B.L.).

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K.H.W., A.C. and D.B.L. devised the analysis and wrote the manuscript. K.H.W. performed computational modelling and validated the data. K.H.W. and S.Z. processed the data. D.B.L. supervised the project.

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Extended data figures and tables

Extended data fig. 1 proportions of faculty without doctoral degrees..

Each transparent circle represents one of 107 fields, coloured and grouped by domain. Filled grey circles represent domain-level estimates. A single blue circle (left) represents U.S. academia overall. Fields for which more than 10% of faculty do not have a doctorate are annotated

Extended Data Fig. 2 University network centrality as a function of prestige.

Lines are coloured by domain, and show the mean geodesic distance through links in the faculty hiring network from the university at that prestige rank to every other university, divided by the diameter of the network. Smaller values toward the left side indicate that more prestigious universities are more centrally located in each faculty hiring network; less prestigious universities are more peripherally positioned. All universities belong to the network’s strongly connected component by construction (Methods)

Extended Data Fig. 3 Self-hire rates as a function of prestige and career age.

Logistic regression coefficients, expressed as change in log-odds of being a self-hire for a one-decile increase in prestige, stratified by domain (colours) or academia (blue), and by four bins of career age as indicated. Circles, significant by two-sided t-test, Benjamini-Hochberg corrected p < .05; crosses, not significant

Extended Data Fig. 4 Effects of prestige.

Logistic regression coefficients, expressed as a change in log-odds of faculty being a self-hire (a), being a non-U.S. faculty (b), or a woman (c) for a one-decile increase in prestige, stratified by domain (colours) and academia (blue), for newly hired faculty (filled symbols) and for existing faculty (hollow symbols) and connected by a line. Circles, significant (two-sided t-test, Benjamini-Hochberg corrected p  > 0.05); crosses, not significant. (a) Existing faculty are more likely to be self-hires at more prestigious universities, but this effect attenuates or disappears for new hires, indicating that the positive relationship between self-hiring and prestige is likely driven by attrition. (b) Newly hired faculty are more likely to hold a non-U.S. doctorate than existing faculty. This likely results from higher rates of attrition among faculty with a non-U.S. doctorate (Fig. 1c ). (c) We observe no universal relationship across domains between prestige and gender, but both new and existing faculty are somewhat more likely to be men as prestige increases for academia as a whole

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Reporting summary, peer review file, source data fig. 1., source data fig. 2., source data fig. 3., source data fig. 4., source data fig. 5., source data fig. 6., source data extended data fig. 1., source data extended data fig. 2., source data extended data fig. 3., source data extended data fig. 4., rights and permissions.

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Wapman, K.H., Zhang, S., Clauset, A. et al. Quantifying hierarchy and dynamics in US faculty hiring and retention. Nature 610 , 120–127 (2022). https://doi.org/10.1038/s41586-022-05222-x

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• How much does affordable health insurance improve people’s health? 
• How can poor countries eradicate poverty? 

There are many different subfields within economics, including, but not limited to behavioral, econometrics, energy/environmental, development, financial, international, monetary, public, and urban economics. You can familiarize yourself with the latest work in economics by subscribing to working paper series, such as NBER’s New This Week or the New York Fed’s Staff Reports . To get an idea of the breadth of questions economists can answer, you could listen to Stephen Dubner’s “ Freakonomics Radio ” podcast. You may also want to explore the Journal of Economic Perspectives , the New York Fed’s Liberty Street Economics blog, VoxDev , or VoxEU .  

What Is a PhD Program Like?    

Economics PhD programs typically last five to seven years. Unlike masters programs, they are often fully funded with a stipend, though most require students to complete teaching assistant and/or research assistant (RA) work as part of their funding package. In the first two years, students take classes, many of which are mathematically demanding. The rest of the program can include additional classes but is primarily devoted to original research with the aim of producing publishable papers that will constitute the dissertation.  

Faculty advisors are a central part of PhD programs, as students look to them for guidance during the research process. Economics PhD programs are offered within university economics departments, but there are similar programs in public policy and business schools. You can look at their websites to understand any differences in coursework and subsequent job placements. 

What Can You Do with an Economics PhD?  

Upon graduation, students can obtain jobs in a variety of industries. Many PhD students hope to become university professors. Governments and public policy-related institutions such as the Federal Reserve System, the U.S. federal government, the World Bank, and the International Monetary Fund (IMF) also hire economists to work on policy, lead programs, and conduct research. Finally, economics PhD graduates can also find employment at a variety of private sector companies, including banks, economic consulting firms, and big tech companies. The pay for these different positions can vary. According to the American Economics Association (AEA), the average starting salary for economics assistant professors in 2022-23 was approximately $140,000 at PhD granting institutions and $98,000 at BA granting institutions. 

Programs often publish the placements of their PhD graduates, so you can look online to see specific employment outcomes. See, for example, the University of Maryland’s placements . Ultimately, economists are highly regarded as authorities on a variety of topics. Governments, nonprofits, philanthropic foundations, financial institutions, and non-financial businesses all look to economists to answer important questions about how to best achieve their goals. Thus, earning an economics Ph.D. can potentially help you to influence issues that are important to you. 

Preparing for an Economics PhD Program  

There are several components to an economics PhD program application: college transcripts, GRE scores, letters of recommendation, and personal statements. Please download the Appendix linked below to learn more about transcripts and letters of recommendation. The Appendix details ways in which you can select coursework, obtain research experience, and develop relationships to position yourself for success as a PhD applicant.  

If you feel that you are too far along in your academic career to take enough of the classes described in the Appendix, this does not necessarily preclude you from pursuing an economics PhD. For example, it’s possible to take some of these classes through a master’s program, or through a pre-doctoral RA job. Some pre-doctoral RA jobs, such as the one here at the New York Fed , may enable you to take classes in preparation for graduate school. If you are concerned about your transcript, reach out to an economist at your university for advice; program standards for coursework and grades vary, and it’s a good idea to get more personalized advice. 

Research Experience   

If you’re interested in becoming an economics researcher and applying to PhD programs, it’s best to get research experience as soon as possible. Working as an RA is a great way to learn how to conduct research and get a better idea of whether it’s the right career path for you. Additionally, it can help you obtain a letter of recommendation for graduate school applications and improve your qualifications.  

All types of academic research can be enriching, but it’s beneficial to gain experience working directly with an economist. To find a position, you can reach out to professors whose work you find interesting or find an RA program at your school. Typical RA tasks may involve data collection and cleaning, as well as running analyses and creating charts to represent results. This is where coding skills become crucial; having taken math, statistics, and econometrics courses will also enable you to take on more responsibilities. 

You may also have the opportunity to conduct your own research, possibly under the supervision of a professor at your university. This research could be self-initiated or part of a course such as a thesis workshop. Self-directed research is a great opportunity to learn about all stages of the research process. It’s also an excellent opportunity to create a writing sample for graduate school applications. Ultimately, though, your motivation for conducting your own research project should be that you want to answer a question.  One thing economists have in common is a love of answering questions using data and theory. 

Research experience is also often obtained after completing an undergraduate or master’s degree. Taking on a full-time RA position before applying to PhD programs is very common and can make you a more competitive applicant. You may either get an RA job working for a professor or participate in a pre-doctoral RA program.  

Research assistant programs are more structured than positions with individual professors or projects, which could be helpful. Universities, parts of the government, think tanks, research organizations, and the Federal Reserve System are all good places to look for research assistant programs. To help you decide which opportunities are most desirable, you may want to ask potential employers : Where do people in this program tend to go afterward? Will I be working directly with an economist? How much of my time will be spent on academic research work? Will I be able to take classes as part of this program? Considering whether an economist will be able to evaluate your performance is an important factor for recommendation letters. The ability to take classes, either through tuition reimbursement or waivers, can also be an important benefit. 

The Research Analyst program here at the Federal Reserve Bank of New York is one example of these programs and you should check it out here . The Federal Reserve Board of Governors also has a large program, and many other regional Federal Reserve Banks have similar programs. In addition, the PREDOC website and the  NBER post listings of RA opportunities. J-PAL and IPA also tend to recruit RAs for economic development projects. Another source of RA opportunities is the @econ_ra account on X. 

Who Should Get a PhD in Economics?  

A PhD may not be for everyone, but it is for anyone—people of all genders, religions, ethnicities, races, and national origins have PhDs in economics. Many economists majored in economics, but others majored in math, physics, or chemistry. Because economics is such an integral part of policymaking, it is important that economists come from a wide range of backgrounds so policy can be stronger and more effective. The inclusion of differing perspectives helps ensure that the contribution of economists to work in public policy, academia, and beyond effectively serves the broadest range of society. 

• Coursework Appendix

Kasey Chatterji-Len is a research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.

Anna Kovner  is the director of Financial Stability Policy Research in the Bank’s Research and Statistics Group.

How to cite this post: Kasey Chatterji-Len and Anna Kovner, “Thinking of Pursuing a PhD in Economics? Info on Graduate School and Beyond,” Federal Reserve Bank of New York Liberty Street Economics , May 31, 2024, https://libertystreeteconomics.newyorkfed.org/2024/05/thinking-of-pursuing-a-phd-in-economics-info-on-graduate-school-and-beyond/.

You may also be interested in: AEA: Resources for Students

PREDOC: Guidance for Undergraduates

RA Positions-Not at the NBER

Disclaimer The views expressed in this post are those of the author(s) and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author(s).

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Liberty Street Economics features insight and analysis from New York Fed economists working at the intersection of research and policy. Launched in 2011, the blog takes its name from the Bank’s headquarters at 33 Liberty Street in Manhattan’s Financial District.

The editors are Michael Fleming, Andrew Haughwout, Thomas Klitgaard, and Asani Sarkar, all economists in the Bank’s Research Group.

Liberty Street Economics does not publish new posts during the blackout periods surrounding Federal Open Market Committee meetings.

The views expressed are those of the authors, and do not necessarily reflect the position of the New York Fed or the Federal Reserve System.

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EDI Spotlight: Michael Boyce, PhD

After first joining Duke’s faculty in 2012, it didn’t take Michael Boyce, PhD, long to get involved in equity, diversity, and inclusion work — not only within his department but also on the national scene. In this month’s EDI Spotlight, Boyce, an associate professor, shares how his passion for the work led him to be actively involved with the Department of Biochemistry’s EDI committee since its inception. Additionally, he has become a leader of a national program that seeks to transition scientists from diverse backgrounds into tenure-track research faculty jobs across the country. He also tells us about his love of travel, including a few upcoming international trips with his partner.

You are an associate professor of biochemistry whose research focuses on mammalian cell signaling through protein glycosylation. What does a typical day for you look like?

One thing I like about my job is that every day is different. Of course, research and the people in my lab are a major focus, so I’m often meeting with students, postdocs, and staff, individually or in groups, to discuss data, plan strategy, troubleshoot, write grants or papers, etc. I also enjoy teaching (particularly small-group seminars for PhD students) and service, much of which is focused on graduate education and equity, diversity, and inclusion (EDI) in my case. Another thing I value about my job is that it entails both work within my subject matter (e.g., with colleagues in the Biochemistry Department or globally in the glycobiology field) and interactions with colleagues in other fields from around Duke and through national organizations, such as the American Society for Cell Biology (ASCB).

Aside from your responsibilities as a researcher, you also have been actively involved in equity, diversity, and inclusion initiatives within the Department of Biochemistry. What are some of those initiatives? How and why did you first become involved in EDI in your department?

I’ve been involved in EDI efforts in Biochemistry since 2013, soon after I began at Duke in October 2012. A lot of credit for this goes to Dick Brennan , our department’s longtime chair. He created an EDI committee in the department in 2013, which I have continuously served on and co-chaired over the years. Dick has steadfastly supported and valued our committee’s contributions to the department – not in a merely performative way, but by committing his actions and department resources (money) to empower our activities.

True story: I visited another university a couple months ago to give an invited seminar on my research. In a one-on-one meeting with a new junior faculty member there, he saw on my CV that I had been on the EDI committee for Duke Biochemistry since 2013, and he was impressed and wondered if our committee was the first in the nation (!). I’m not sure we quite hold that record, but I think this reaction speaks volumes about the longstanding commitment that Dick and many students, postdocs, staff and faculty members have contributed to our department’s committee over the years.

You currently serve as co-director of the Maximizing Opportunities for Scientific and Academic Independent Careers (MOSAIC) program, which is designed to facilitate the transition of promising postdoctoral researchers from diverse backgrounds. Tell us a little about the MOSAIC program and what motivated you to get involved.

I’m so fortunate to be involved in MOSAIC, which I think is a tremendously valuable and impactful program. The mission of the NIH MOSAIC program is to increase the diversity of tenure-track biomedical faculty at research-intensive universities nationwide. MOSAIC aims to achieve this goal through two related mechanisms: 1) K99/R00 fellowships that support the postdoc-to-faculty transition of extremely talented scholars who increase diversity and inclusions through their lived experience and/or their service activities, and 2) UE5 awards to scientific societies, which create cohort-based programs to provide skills development, professional networking, and other support to groups of MOSAIC scholars. I have co-directed the ASCB UE5-funded MOSAIC program since its inception, and I work closely with our 50+ rock-star K99/R00 scholars, who continually impress me with their accomplishments.

What impact has the MOSAIC program had since it began in 2020? How has it enhanced diversity within the academic biomedical research workforce?

As the National Institute of General Medical Sciences (NIGMS) and NIH in general have wisely recognized, diversifying the biomedical workforce is good for the United States because it helps us maximize the talent flowing into our scientific enterprise, and it better serves the population of our country, providing intellectual and professional opportunities for as many people as possible.

Already, dozens of our MOSAIC scholars in the ASCB program have taken outstanding faculty positions at great institutions around the country, and many more are in the pipeline. This is also true for the scholars in the other UE5 organizations, beyond ASCB. In other words, MOSAIC has helped to place and support scores of scholars of highly diverse backgrounds in influential, tenure-track faculty positions across the US. The impact of the program will therefore ramify for decades, as these scholars do great science and teach and train tens of thousands of students, postdocs, and other learners.

Closer to home, MOSAIC also has strong ties to Duke through several scholars, such as Duke Neurobiology alum Erica Rodriguez, former Duke postdoc and current NCSU faculty member Ian Williamson, and current Duke faculty member Asiya Gusa . Suzanne Barbour (Dean of the Graduate School) and Gustavo Silva (Associate Professor of Biology) are also involved in other MOSAIC UE5 programs. I hope Duke will hire more MOSAIC scholars as faculty in the future (looking at you, administrator colleagues!) and I hope anyone interested in learning more will check out the NIGMS MOSAIC page and the ASCB MOSAIC Program website.

What passions or hobbies do you have outside of work?

I try to prioritize work-life balance, but I have to admit that my hobbies are maybe a little bit pedestrian! I always make time for exercise (so important for both mental and physical health), and I love cooking, eating, and traveling with my partner, Solomon. This year, we’re fortunate to have trips to Mexico and several countries in South America.