What is a Research Scientist?

Learn about the role of Research Scientist, what they do on a daily basis, and what it's like to be one.

  • What is a Research Scientist
  • How to Become
  • Certifications
  • Tools & Software
  • LinkedIn Guide
  • Interview Questions
  • Work-Life Balance
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  • Resume Examples
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Definition of a Research Scientist

What does a research scientist do, key responsibilities of a research scientist.

  • Designing and implementing rigorous experiments to test hypotheses and solve complex problems.
  • Collecting, analyzing, and interpreting data using statistical techniques and specialized software.
  • Writing research papers, reports, and reviews for publication in scientific journals and presentations at conferences.
  • Applying for funding and grants to support research projects and initiatives.
  • Collaborating with interdisciplinary teams of scientists and professionals to enhance research quality and applicability.
  • Staying current with the latest scientific advancements and literature in their field of expertise.
  • Developing and testing new scientific methods and technologies to improve research efficiency.
  • Mentoring and supervising junior researchers, technicians, and graduate students.
  • Ensuring all research activities are conducted in compliance with ethical and regulatory standards.
  • Reviewing and providing feedback on the work of peers to validate research findings and proposals.
  • Communicating with stakeholders, including industry partners, government agencies, and academic institutions.
  • Translating research discoveries into practical applications and products for industry or societal use.

Day to Day Activities for Research Scientist at Different Levels

Daily responsibilities for entry level research scientists.

  • Conducting experiments and recording detailed observations
  • Assisting with literature reviews and data collection
  • Performing basic data analysis and interpretation
  • Maintaining laboratory equipment and ensuring supplies are stocked
  • Participating in lab meetings and presenting findings
  • Complying with lab safety protocols and regulatory requirements
  • Receiving training in research methodologies and best practices

Daily Responsibilities for Mid Level Research Scientists

  • Designing and leading their own experiments or sub-projects
  • Writing grant proposals and securing funding for research
  • Authoring and co-authoring scientific papers and reports
  • Presenting research findings at conferences and seminars
  • Collaborating with cross-functional teams within and outside the organization
  • Mentoring entry-level scientists and research assistants
  • Contributing to the development of research strategies and objectives

Daily Responsibilities for Senior Research Scientists

  • Leading and managing major research projects and collaborations
  • Developing and directing research strategies and priorities
  • Mentoring and supervising mid-level scientists and research teams
  • Securing substantial funding and managing budgets for research activities
  • Establishing partnerships with industry and academia
  • Advising on policy and contributing to the broader scientific community
  • Reviewing scientific manuscripts and serving on editorial boards

Types of Research Scientists

Theoretical research scientist, experimental research scientist, clinical research scientist, data research scientist, applied research scientist, environmental research scientist, what's it like to be a research scientist , research scientist work environment, research scientist working conditions, how hard is it to be a research scientist, is a research scientist a good career path, faqs about research scientists, how do research scientists collaborate with other teams within a company, what are some common challenges faced by research scientists, what does the typical career progression look like for research scientists.

How To Become a Research Scientist in 2024

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Research scientist: job description

targetjobs editorial team

Last updated: 7 Feb 2024, 16:47

Research scientists are responsible for designing, undertaking and analysing information from controlled laboratory-based investigations, experiments and trials.

Supported by:

The Science and Technology Facilities Council (STFC)

Research scientist

You could work for government laboratories, environmental organisations, specialist research organisations or universities.

What does a research scientist do? | Graduate salaries | Typical employers | Qualifications and training | Key skills

Research scientists work in almost every area of science imaginable. They plan and carry out experiments and investigations in a range of areas, including geoscience, medical research, meteorology and pharmacology. These are broad research areas; a research scientist will most likely be working on a much more specialist topic, such as gravitational waves or stem cell biology. If your specialism is likely to be chemistry-based, take a look at our research chemist job description.

A research scientist's work is almost entirely laboratory-based, with responsibilities that include:

  • planning and conducting experiments
  • recording and analysing data
  • carrying out fieldwork, eg collecting samples
  • presenting results to senior/other research staff
  • writing research papers, reports, reviews and summaries
  • demonstrating procedures
  • preparing research proposals and funding applications/bids
  • supervising junior staff including technicians
  • organising product/materials testing
  • ensuring that quality standards are met
  • liaising with research and/or production staff
  • developing original solutions to problems
  • keeping up to date with relevant scientific and technical developments

What will I earn as a research scientist?

Graduate programmes with science employers usually offer a salary of around £25,000. With experience, you could earn around £35,000 to £40,000, depending on your experience.

Where do research scientists work?

Typical employers of research scientists include:

  • Government laboratories
  • Environmental agencies
  • Utilities providers
  • Specialist research organisations and consultancies
  • Public funded research councils
  • Universities
  • Private food companies
  • Materials companies
  • Consumer products companies
  • Pharmaceuticals producers
  • Chemical companies.

Research posts, particularly those with permanent contracts, attract strong competition. Science graduate jobs are advertised online, by careers services, in national newspapers, in relevant scientific publications such as New Scientist , Science , Nature , Chemistry World and in journals published by the professional institutions. Speculative applications are advisable, for which directories such as Current Research in Britain may be useful.

The recruitment process is likely to involve a technical interview. Read our article on technical interviews to find out what these involve and how you can tackle them.

What qualifications do I need to be a research scientist?

You can only become a research scientist if you have a good degree (a 2.1 or above) in a science subject.

A relevant postgraduate qualification (a PhD/research-based MSc) is also normally required, particularly for permanent positions. Post-doctoral research and/or practical research/laboratory work experience is also beneficial, and frequently required for academic posts. Read our article on scientific postgraduate study to explore your different options.

What skills do research scientists need?

  • Determination
  • Scientific and numerical skills
  • Flexibility
  • Decisiveness
  • A logical and independent mind
  • Meticulous attention to detail and accuracy
  • Excellent analytical skills
  • Teamwork skills
  • Interpersonal skills
  • Written and oral communication skills.

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Research Scientist skills for your resume and career

Research Scientist Example Skills

One of the most important hard skills required to be a research scientist is data analysis. Data analysis is a crucial skill because it helps make sense of scientific research. Research scientists also need to have the hard skill of knowledge of procedures and the potential ability to train others on these procedures.

On the other hand, the soft skills that are crucial for a research scientist are curiosity, organizational skills, and a strong sense of interpersonal skills. As Rev. Grace Song , the Won Buddhist Studies Department Chair at Won Institute, so aptly puts it, "Clear communicator, good time management skills, ability to resolve conflicts, self-aware, values collaboration" are all soft skills every research scientist should possess.

15 research scientist skills for your resume and career

Python is a popular programming language used by researchers to analyze and visualize data. Research scientists use Python to automate data processing, integrate with other software, and script data analysis pipelines. They also use Python to fit algorithms to data and implement machine learning techniques. As Dr. Joey Neilsen , Assistant Professor at Villanova University, puts it, "Our students take a year of Computational Physics in Python, and we integrate Python into some of our upper-level courses and labs as well."

  • Created open-source data analysis and visualization package in Python.
  • Coded a class that integrated OpenGL with Python and C++ to simulate chaotically dynamic system.

2. Data Analysis

Data analysis is the process of examining and interpreting data to draw conclusions. Research scientists use data analysis extensively, including coordinating tests, collecting data, and conducting operational tests. They also use data analysis software to analyze human genome sequence data. They perform data analysis to generate specific analysis reports for various material samples, and they collaborate with other programs to monitor and analyze data. As Jay Tischfield , Executive Director at Rutgers University's Department of Genetics, puts it, "Computational and data analysis skills are crucial for quantitative analysis of biological data."

  • Worked extensively with data analysis/interpretation and presentation.
  • Coordinated associated test-planning, developed test planning documents, conducted operational tests, conducted data analysis, and developed reporting documents.

3. Patients

Patients are individuals who receive medical care or treatment. Research scientists use patients in various ways, such as studying blood cell formation and function, identifying disease-specific antibodies, and transcribing patients' interviews. They also use patients to investigate medical device implants, develop new cancer drugs, and analyze PET data for Parkinson's disease patients. As Bart Elmore , Associate Professor of Environmental History at Ohio State University, puts it, "I'm not sure people think of history this way, but the truth is, knowing how to digest historical data and translate it into useful information that can help guide decisions in the present is what historians do."

  • Participated in laboratory and clinical research designed to provide clinically-relevant insights into blood cell formation and function in cancer patients.
  • Developed a computer-based patient model to identify high risk, early intervention patients and reduce medical costs.

C++ is an object-oriented programming language used for developing applications, systems software, and games. Research scientists use C++ to simulate the mechanical behavior of composites, analyze large data volumes, and create software for monitoring performance. They also use C++ to develop ML algorithms for various purposes and to create software for physics data statistical analysis.

  • Implemented C++ capabilities to simulate the effective mechanical behavior of rubber-metal composites within an in-house Finite Element software.
  • Performed extensive waveform analysis using C++ to characterize light sensor performance that led to defining detector design requirements.

5. Research Projects

Research projects are original investigations that add to scientific knowledge. Research scientists use research projects to evaluate the efficacy of technology-based interventions, develop biological assays for cancer research, and identify and establish clinical collaborations. They design and perform primary research projects, provide technical support and training, and develop statistical analysis strategies. They also supervise intern students, laboratory technicians, and undergraduate students in their research projects.

  • Dedicated to continued enhancement of leadership competencies, problem solving, independent evaluation of scientific data for basic research projects.
  • Identified and established novel clinical collaborations with academic centers, researchers and physicians that could support research projects.

6. Chemistry

Chemistry is the scientific study of the composition, structure, and properties of substances and the transformations they undergo. Research scientists use chemistry to develop new synthetic pathways to complex molecular targets, monitor water chemistry, and perform scientific experiments in a chemical research setting. They also utilize biochemical assays and isolation chemistry techniques to identify drugs for use in drug discovery programs. As Dr. Richard Knight Ph.D. , a Teaching Professor and Associate Department Head at Drexel University, puts it, "A significant number of MSE majors do, however, pursue a broad range of minors in addition to their MSE major. Popular minors include ... Chemistry."

  • Process Chemistry Safety Steward/Safety Mentor/E-Team member
  • Specialized in synthetic methodology, chemistry optimization, and the development of new synthetic pathways to complex molecular targets.

Choose from 10+ customizable research scientist resume templates

Java is a programming language that allows developers to create interactive computer and mobile applications. Research scientists use Java for a variety of purposes. They use it to develop graph analysis algorithms, implement network vulnerability removal and hardening, and create Internet image commerce systems. They also use it to design and develop interactive network topology layout tools and Solar Power Forecasting systems.

  • Developed the camera take detection service via java and integrated it into an automatic video object annotation system utilizing social cues.
  • Research Scientist Worked with the Java Tools research group designing advanced interactive programming and visualization tools; explored agent-based component architectures.

8. Molecular Biology

Molecular biology is the study of the structure, function, and interactions of biological molecules like DNA and proteins. Research scientists use molecular biology to study the genetic and molecular mechanisms underlying various biological processes. They design and execute experiments, analyze data, and collaborate with other experts to advance our understanding of biological systems. According to Darrell Fry , Associate Professor at Stephen F. Austin State University, "Earning a degree from an University that takes time and effort to be accredited by either the American Chemical Society (ACS) and/or the American Society for Biochemistry and Molecular Biology(ASBMB) ensures the graduate will have marketable skills."

  • Created/established molecular biology laboratory within department.
  • Design and execute molecular biology and biochemistry studies to support project objectives with minimal direct supervision from Research Director.

9. Data Collection

Data collection is the process of gathering information from various sources. Research scientists use data collection to identify and determine methods, procedures, and techniques that support research design. They also participate in data collection by coordinating study sites, administering research instruments, and conducting qualitative interviews. Data collection is an essential part of research, as it allows research scientists to analyze and interpret data and monitor the progress of their projects.

  • Identified and determined methods, procedures, and techniques to support research design; identified and recommended data collection methodology.
  • Participate in data collection, including coordination of study sites, administration of research instruments, and conducting qualitative interviews.

10. Cell Culture

Cell culture is a laboratory technique used to grow cells outside of an organism. Research scientists use cell culture to study cells and their behavior, develop new therapies, and test the effects of different substances on cells. They isolate and prepare primary cells, like T-cells, and perform cell culture to develop personalized therapies. They also create standard operating procedures for mammalian cell culture and viral antigen production, and optimize cell culture conditions for antibody expression and purification. They use automated cell culture robotics to improve efficiency and practice aseptic techniques to maintain clean environments.

  • Conducted isolation and preparation of primary cells including T-cell and performed primary cell culture for developing personalized therapies.
  • Created and implemented standard operating procedures on mammalian cell culture and viral antigen production.

11. TensorFlow

TensorFlow is a popular open-source machine learning library. Research scientists use TensorFlow to develop neural networks for tasks like document classification. For example, one research scientist used TensorFlow to develop a convolutional neural network sentence classifier.

  • Project: Convolutional Neural Network for document classification (2016.10-2017.1) - Develop a convolutional neural network sentence classifier using Tensorflow.

12. Visualization

Visualization is the process of creating a visual representation of data or information. Research scientists use visualization to help them analyze and understand large data sets. They use software such as Tableau, Matlab, and IDL to create visually appealing graphs and charts that help them identify trends and patterns in the data. This allows them to make more informed decisions and draw conclusions about their research.

  • Research includes developing robust and adaptive systems for computer-aided analysis and visualization with machine learning and image processing/computer vision approaches.
  • Manage the development of innovative visualization and concept mapping of contested environment analysis challenges and analyst skill sets.

13. Excellent Interpersonal

Excellent interpersonal skills are crucial for research scientists. They use these skills to interact with diverse populations and create a comfortable environment when conducting research. Research scientists also use their excellent interpersonal skills by interacting with various departments within research facilities.

  • Utilized excellent interpersonal and empathetic skills while interacting with a diverse population, creating a comfortable environment.
  • Team oriented professional with excellent interpersonal and communication skills.

14. Laboratory Equipment

Laboratory equipment refers to tools and instruments used for conducting experiments and procedures in a laboratory. Research scientists use laboratory equipment to perform a wide range of tasks, such as measuring and analyzing data, conducting experiments, and maintaining supplies. They also supervise and train others on how to operate this equipment, troubleshoot issues, and perform routine maintenance. As a research scientist, laboratory equipment plays a crucial role in conducting research and advancing scientific knowledge.

  • Managed maintenance/upgrades of laboratory equipment.
  • Supervised and trained post-doctorate fellows, students and lab assistants to perform general laboratory techniques and operate laboratory equipment.

15. Experimental Design

Experimental design refers to the process of creating a plan for data collection. Research scientists use experimental design to manage the day-to-day operations of critical projects and perform advanced analysis. They also use it to optimize product development and marketing decisions by applying statistical analysis to laboratory and consumer research. As Dr. Bobby Burkes , Interim Department Head/Professor at Grambling State University, puts it, "The ability to communicate (convey and express ideas) in a direct and remote setting is becoming an essential asset. The ability interact with and possibly develop simulations of experimental design and process flow paths are also technical skills that are in demand in most industries."

  • Managed investigations from incident to CAPA closure including experimental design, collaboration with team members, and organizing and reporting results.
  • Contributed scientific expertise to critical projects, manage the day-to-day operations of those initiatives and perform advanced analysis and experimental design.

12 Research Scientist Resume Examples

Build a professional research scientist resume in minutes. Browse through our resume examples to identify the best way to word your resume. Then choose from 12 + resume templates to create your research scientist resume.

What skills help Research Scientists find jobs?

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What type of skills will young Research Scientists need?

Professor, Pharmacology & Toxicology; Professor, Obstetrics & Gynecology, Wright State University

What soft skills should all Research Scientists possess?

Alexandra (Sasha) Ormond Ph.D.

Associate Professor of Chemistry, Director of Dual Degree Engineering, Meredith College

What hard/technical skills are most important for Research Scientists?

What skills stand out on research scientist resumes, what research scientist skills would you recommend for someone trying to advance their career.

Assistant Department Chair, Geology, Auburn University

List of research scientist skills to add to your resume

Research Scientist Skills

The most important skills for a research scientist resume and required skills for a research scientist to have include:

  • Data Analysis
  • Research Projects
  • Molecular Biology
  • Data Collection
  • Cell Culture
  • Visualization
  • Excellent Interpersonal
  • Laboratory Equipment
  • Experimental Design
  • Statistical Analysis
  • Flow Cytometry
  • Prototyping
  • Product Development
  • Research Findings
  • Technical Reports
  • Drug Discovery
  • Next-Generation Sequencing
  • Method Development
  • Analytical Methods
  • Distributed Computing
  • Clinical Trials
  • Cell-Based Assays
  • Western Blotting
  • Technical Support
  • Emerging Technologies

Updated February 16, 2024

Editorial Staff

The Zippia Research Team has spent countless hours reviewing resumes, job postings, and government data to determine what goes into getting a job in each phase of life. Professional writers and data scientists comprise the Zippia Research Team.

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Northeastern University Graduate Programs

How to Become a Research Scientist

How to Become a Research Scientist

Industry Advice Science & Mathematics

Professionals with a background in biotechnology can choose to pursue many lucrative careers . One of the most common choices is to become a research scientist. These individuals work in drug and process development, consistently conducting research and performing experiments to help move the biotechnology industry forward. 

“At the highest level, a research scientist is somebody who can design and execute experiments to prove or disprove a hypothesis,” says Jared Auclair , director of the biotechnology and bioinformatics programs at Northeastern. “Within the world of biotechnology, that can mean a number of different things, from creating new drugs to improving the process of how we make a drug.”

Professionals in this industry are often drawn to the wide array of applications of this work, as well as the consistently positive career outlook. The average salary of a biotechnology research scientist is $85,907 per year, with plenty of opportunities for increased salary potential depending on specializations, location, and years of experience. 

These factors—alongside the growing demand for advancement in biotechnology over the last few decades—have led many aspiring biotechnologists to consider a career in research science. Below we offer five steps professionals can take to kick-start a career in this field.

Download Our Free Guide to Advancing Your Biotechnology Career

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5 Steps to Become a Research Scientist

1. acquire the necessary technical skills..

According to Auclair, there are four main applications of research science within the biotechnology field:

  • Molecular Biology
  • Process Science
  • Biochemistry
  • Analytical Biotechnology

Professionals hoping to pursue a career in research science must begin by deciding which of these four areas is the best fit for their interests and backgrounds. They must then acquire the specific skill sets they need to excel in that area. 

Below, Auclair breaks down some of the key skills and knowledge required within each of these specializations:

  • Molecular biologists should focus on developing a complex understanding of DNA and learn how to do a Polymerase Chain Reaction alongside other DNA-related experiments. 
  • Process scientists must understand cell biology and how to work with living mammalian cells, as well as how to perform analytical experiments using mass spectrometry and other analytical tools.
  • Biochemists should focus on obtaining the skills necessary to make a protein drug, including the expression and purification of proteins.
  • Analytical biotechnicians must become comfortable with techniques like mass spectrometry—a process that uncovers what drug products are at a molecular level.

One efficient way aspiring research scientists can obtain these specific skill sets is to pursue a master’s degree in biotechnology at a top university like Northeastern. 

“The biotech program is designed in collaboration with industry so that we’re meeting their needs,” Auclair says. “This includes training students with the skills they need to be a successful research scientist.”

The curriculum of Northeastern’s program explores the core competencies required to excel in the general biotechnology field and provides students with the unique subsets of skills they need to specialize in a specific area of research science. Students can even declare one of 10 industry-aligned concentrations, including options that directly relate with these common research science roles.

“Especially in industry, most people who are doing research science—who are actually doing the experiments and helping think about experiments with some of the senior leaders in the company—are people with a master’s degree,” Auclair says.

2. Become a critical thinker.

Alongside honing technical skills, Auclair says that critical thinking abilities are key for aspiring research scientists. 

“It’s important to become a critical thinker and a problem solver, and to challenge yourself wherever you can to step outside of your comfort zone,” Auclair says. 

Though critical thinking is a common requirement among most professional career paths, it is especially important for research scientists, who are constantly tasked with innovating and thinking creatively to solve problems.

Northeastern’s master’s in biotechnology program is designed to help students grow in this regard. “Everything we do within the program is geared [toward] making you a critical thinker and a problem solver,” Auclair says. “We try to define classes and assessments to make you think, [and] we also hire most of the faculty in our program directly from the industry, so they bring with them real-world experience that they can talk about with the students.”

These real-world case studies are a core component of Northeastern’s approach to learning, and they help prepare students to think critically about their work. By bringing this exposure into the classroom, students also graduate better prepared to tackle current industry challenges and adapt to evolving trends .

3. Hone your “power skills.”

It’s no longer enough for research scientists in biotechnology to have obtained the technical skills needed to complete their work. Today, many employers require an array of industry-specific “power skills”—previously known as “soft skills”—among candidates for research science roles.

Below we explore the top three “power skills” for biotechnology research scientists:

  • Communication: As a research scientist, “you must be able to communicate scientific information to both technical and non-technical people,” Auclair says. For this reason, professionals should work to hone their verbal and written communication styles, focusing specifically on the variances in each depending on which audience they’re interacting with.
  • Presentation Ability: Research scientists must be able to present their findings clearly and concisely to a variety of different audiences, ranging from fellow scientists to investors to C-suite executives. Research scientists must be comfortable in front of a group and know how to speak about their experiments and conclusions in an engaging and informative way.
  • Teamwork: Although one might think a research scientist’s work is very siloed, today’s professionals must be very comfortable working with others in a lab environment. They must become comfortable sharing ideas, providing feedback to others in their cohort, and tweaking their experiments based on contributed findings.

Northeastern offers students the chance to explore each of these core “power skills” during their time within the master’s in biotechnology program. For example, the university offers countless opportunities for students to collaborate with and present to classmates, instructors, and even industry-leading organizations through Northeastern’s experiential learning opportunities, giving them the chance to apply these skills in both classroom and real-world situations early on.

Learn More: How to Become a Biotechnologist: Build Your Soft Skills

4. Obtain hands-on experience.

One of the most effective ways an aspiring research scientist can prepare for a career in this field is to obtain experiences working in a real lab. While finding these kinds of opportunities can be difficult for those just breaking into the field, programs like Northeastern’s MS in biotechnology bake hands-on learning directly into the curriculum. 

“Students do essentially four to six months [working in the] industry, and put what they learn in the classroom…into practice,” Auclair says.

These opportunities, known as co-ops , provide students with the chance to work within top organizations in the industry and explore the real-world challenges of the field from inside a functioning lab.

Did You Know: Northeastern’s program provides students with exposure to the tools and equipment used within labs in the industry. This access to cutting-edge technology reduces the learning curve and allows students to dive into their work as soon as they graduate.

Another unique way Northeastern provides hands-on experience is through Experiential Network (XN) Projects . Students who participate in these projects are typically paired with a sponsor from an active biotech company that has a real-world problem they need to solve. Then, “under the guidance of a faculty member, students spend the semester trying to come up with solutions to that problem,” Auclair says. “It’s all student-driven.”

Hands-on learning opportunities like these give students a competitive advantage when it comes to applying for jobs. “The experiential learning piece [of our program] is what has our students actually stand out above others in the field,” Auclair says, because employers like to see that their candidates are capable of applying their skills in a real-world environment. 

5. Grow your network.

Research shows that 85 percent of all jobs today are filled through networking, making it more important than ever for professionals across industries to invest time and energy into building these vital relationships.

Professionals hoping to establish a career as a research scientist are no exception. These individuals should aim to develop connections with organizations and individuals within the greater biotech industry early on in their careers, and use those relationships to help carve their path forward.

Northeastern’s master’s in biotechnology program has strategically created many great opportunities for students to network throughout their time in the program. They are encouraged to build relationships with their classmates, guest speakers, faculty, and even the industry leaders they meet through co-ops and XN projects. As a result, they establish various impactful connections with individuals at different stages in their careers, all before they graduate.

Learn More: Networking Tips for Scientists

Another way Northeastern’s program supports networking is through opportunities for student/faculty collaboration. “We encourage our students to interact with our own faculty who are research scientists as much as possible, whether that’s volunteering in their lab or finding a half an hour to talk to them about what they’re doing,” Auclair says. “We want our students to be exposed to as many research scientists as possible while they’re in the program.”

Take the Next Step

Pursuing a master’s degree in biotechnology from a top university like Northeastern is a great way for aspiring research scientists to break into the field. Students in these programs can hone related skill sets, grow their professional networks, and experience hands-on learning, all while pursuing graduate-level education. 

Learn more about how a master’s in biotechnology can set you up for success as a research scientist on our program page , then get in touch with our enrollment coaches who can help you take the first step.

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What do research scientists do.

Wondering what the job is really like for research scientists?

You've come to the right place.

Keep reading to find detailed information about what research scientists do, including the type of work they are tasked with on a daily basis, industries in which they work, and the specific skills needed for a successful career.

Research Scientists Overview & Description

Let's get started with the basics about research scientists by taking a look at a simple description and popular job titles.

Research Scientists conduct research into fundamental computer and information science as theorists, designers, or inventors. Develop solutions to problems in the field of computer hardware and software.

Popular Job Titles For Research Scientists

Sample of reported job titles.

  • Computer Scientists
  • Machine Learning Scientists
  • Staff Scientists
  • Computational Scientists
  • Research Engineers
  • Computer Vision Scientists
  • Machine Learning Research Scientists
  • Research Scientists
  • Applied Scientists
  • Big Data Analysts
  • Cybersecurity Research Scientists
  • Artificial Intelligence/Machine Learning Engineers

Read on for insight into the industries where the highest concentration of jobs for research scientists can be found.

Best Industries for Research Scientists

Research scientists jobs by industry.

  • Federal Government, Civilian: 31.1%
  • Computer Systems Design and Related Services: 28.9%
  • Scientific Research and Development Services: 17.4%
  • Education and Hospitals (State Government): 4.2%
  • Web Search Portals, Libraries, Archives, and Other Information Services: 3.5%
  • Software Publishers: 2.9%

When it comes to jobs in the United States, the largest single category of research scientists can be found working in the Federal Government, Civilian sector. In 2022, about 31.1% of all jobs for research scientists were found there.

Other top industries by percentage include Computer Systems Design and Related Services (28.9%), Scientific Research and Development Services (17.4%), Education and Hospitals (State Government) (4.2%), Web Search Portals, Libraries, Archives, and Other Information Services (3.5%) and Software Publishers (2.9%).

Top Online College For Working Adults

Franklin University is a top choice for adults who need to balance school with busy lives. Founded in 1902 in Columbus, Ohio, Franklin's main focus has been serving adult students and tailoring education to fit their needs. Nonprofit and accredited by the Higher Learning Commission (hlcommission.org/800.621.7440), Franklin offers more than 50 affordable bachelor's, master's, and doctoral programs — all available 100% online.

Degree Options for Research Scientists

Learn to translate business requirements into robust yet functional software applications and database designs to help businesses not only run but thrive, and jump start your career as a user support specialist, computer system analyst, or software developer.

  • Class Type: 100% online
  • Cost Per Credit: $398

Equip yourself for a role as an IT, network or help desk specialist with fundamental technology skills, including medium-scale network administration, small website and application development, and database design and querying.

Go beyond basic programming and develop the technical skills necessary to apply, design, and implement software systems.

Bridge the gap between business and technology and develop the interpersonal skills to become an IT liaison in your organization.

Harness the power of data by creating data-driven strategies and communicating data insights with a B.S. Information Systems-Analytics Focus.

Develop your ability to lead, communicate and make strategic decisions that impact projects and processes with a B.S. Information Systems-Business Analysis & Project Management Focus

Build technical savvy and business acumen that bridges the gap between business and technology with a B.S. Information Systems with a Business Information Systems focus.

Get the knowledge to manage healthcare data, navigate regulations and inform ethical decision-making with a B.S. Information Systems-Healthcare Information Systems Focus

Play a vital role in any business environment by designing and implementing mission-critical infrastructure, security, and servers.

Develop the advanced technical skills needed to turn complex programming specifications into well-designed computer programs.

  • Class Type: Face-to-face, Online coursework
  • Placement Tests: GMAT/GRE not required for admission

Deliver high-quality software that helps companies and organizations maintain data security and integrity with Franklin’s 20-month online M.S. in Computer Science with a focus in Cybersecurity.

  • Months To Complete: 20

Learn to create scalable software systems that Improve organizational effectiveness and efficiency by earning Franklin’s 20-month online M.S. in Computer Science with a focus in Software Systems. The hands-on, theory-to-practice program will prepare you to be an asset in a variety of industries

Earn your M.S. in Information Technology degree 100% online in as few as 16 months.

  • Months To Complete: 16

Earn your M.S. in Information Technology degree with a focus in Data Analytics 100% online in as few as 16 months.

Earn your M.S. in Information Technology degree with a focus in Healthcare 100% online in as few as 16 months.

Earn your M.S. in Information Technology degree with a focus in IT Leadership 100% online in as few as 16 months.

Earn your M.S. in Information Technology degree with a focus in IT Management 100% online in as few as 16 months.

Earn your M.S. in Information Technology degree with a focus in Learning Technology 100% online in as few as 16 months.

Certificates & Microcredentials for Research Scientists

Start your cloud computing journey with AWS certificate courses for beginners and keep up with the fast pace of innovation.

  • Class Type: 100% Online
  • Time To Complete: 1-2 months
  • Cost: $35/month

This DeepLearning AI certificate course lets you dive into the cutting-edge world of AI specialization, machine learning and data-driven solutions.

  • Time To Complete: 3-4 months

In-demand programmers know Git. You can, too, with GitHub certificate courses that put you among the ranks of other Git certification-ready development pros.

Fast track your IT career with the Google IT support training and certificate that helps you learn about network protocols, operating systems, and solving problems using code.

  • Time To Complete: 4-5 months

Put your creativity to work with these Google UX design courses that equip you to build and test user-centered solutions and to use Google Analytics to improve usability.

Develop practical skills in Python and IBM applied AI thanks to deep learning courses that show you how to design, build and deploy AI-powered apps.

Build your cloud developer portfolio with this hands-on IBM full stack cloud developer certificate course that uses the latest tools and technologies to manage full stack cloud native apps.

  • Time To Complete: 5-6 months

What Do Research Scientists Do on a Daily Basis?

So you have a high-level understanding of what research scientists do and the types of industries in which they work - but what do they really do each day?

A great way to understand the type of work research scientists do is to examine actual job postings and focus on the specific skills that employers are seeking. That will help paint a clearer picture of the tasks that research scientists tackle each day.

Continue reading for a breakdown of specialized skills found in job postings for research scientists, as well as common skills - interpersonal qualities and attributes - that can help you thrive in the workplace.

In-Demand Skills for Today's Research Scientists Based on 15,896 job postings

Top 5 specialized skills for research scientists, top 5 common skills for research scientists.

Based on 15,896 job postings related to research scientists, computer science was the top specialized skill sought by employers, with 42% of all postings looking for that skillset. Skills for python (programming language), machine learning, algorithms, data analysis and c++ (programming language) were also highly sought.

As for common skills, research was the most desired skill found in job postings for research scientists, followed by communications, mathematics, innovation, writing and leadership.

Most In-Demand Jobs for Research Scientists

Top 5 posted job titles.

Expand the section below to see unique job postings for all occupations related to research scientists.

Ready to dig deeper into career information for research scientists? Visit our other pages focused on salary and education for research scientists.

All Occupations

The Best Adult Colleges and Careers Guide has compiled data for dozens of in-demand jobs. Explore our full catalog of occupation data by visiting the link below.

About This Data

The Best Adult Colleges & Careers Guide is sponsored by Franklin University, a nonprofit, accredited institution. The guide uses 2022 information from Lightcast™ to provide data on dozens of in-demand jobs.

Job titles used in government data may differ slightly from the job title on this page, so the closest matching government job classification may be used as a proxy to present data here.

On this page, data corresponds to the following occupational classification: Computer and Information Research Scientists.

Copyright 2024 Franklin University

Top 12 Research Scientist Skills to Put on Your Resume

In today's fast-evolving scientific landscape, showcasing a robust set of skills on your resume can significantly elevate your prospects as a research scientist. This article delves into the top 12 skills that not only highlight your expertise and adaptability but also position you as a standout candidate in the competitive field of scientific research.

Top 12 Research Scientist Skills to Put on Your Resume

Research Scientist Skills

  • Machine Learning
  • Data Visualization
  • Bioinformatics (if relevant)
  • Statistical Analysis
  • Quantum Computing (if relevant)
  • CRISPR (if relevant)

Python is a versatile, high-level programming language favored for its readability and broad applicability in scientific computing, data analysis, artificial intelligence, and automation, making it a powerful tool for research scientists.

Why It's Important

Python is important for a Research Scientist because it offers powerful libraries for data analysis, machine learning, and scientific computing, simplifying complex operations and enabling efficient research and innovation.

How to Improve Python Skills

Improving your Python skills as a Research Scientist involves focusing on areas that enhance data analysis, numerical computation, and the efficiency of your code. Here are concise recommendations:

Master Key Libraries : Deepen your understanding of libraries central to scientific computing and data analysis, such as NumPy , SciPy , Pandas , and Matplotlib .

Learn Data Visualization : Enhance your ability to communicate results through visualizations using libraries like Seaborn and Plotly .

Parallel Computing : Familiarize yourself with parallel computing to handle large datasets and speed up your analysis using Dask or Joblib .

Machine Learning : Gain proficiency in machine learning libraries, notably scikit-learn for general algorithms and TensorFlow or PyTorch for deep learning.

Version Control : Use version control systems like Git for tracking changes and collaboration. GitHub offers hosting and more, see GitHub .

Code Efficiency : Learn to write more efficient and faster Python code by understanding advanced Python features and profiling tools. Cython can be particularly useful for increasing the speed of Python code.

Software Carpentry : Explore resources like Software Carpentry that offer lessons on Python aimed at scientists and engineers, covering basics to advanced topics.

Continuous Learning : Stay updated with the latest Python developments and libraries through resources like PyCon , Python Weekly , and ArXiv for the latest research papers.

Improving your Python skills is an ongoing process, involving the continual learning of new libraries, tools, and methodologies to stay at the forefront of research and development.

How to Display Python Skills on Your Resume

How to Display Python Skills on Your Resume

R is a programming language and software environment designed for statistical computing and graphics, widely used among statisticians and data analysts for data analysis and research purposes.

R is important for a Research Scientist due to its extensive statistical analysis and data visualization capabilities, which are essential for analyzing complex data sets, testing scientific hypotheses, and communicating findings effectively.

How to Improve R Skills

Improving your R skills as a Research Scientist involves a combination of learning best practices, coding efficiently, understanding data manipulation and visualization, and staying updated with the latest packages and developments in the R community. Below are concise steps with resources to help you enhance your R proficiency:

Master the Basics : Ensure a strong foundation by thoroughly understanding the basics of R. The R for Data Science book by Hadley Wickham & Garrett Grolemund is an excellent start.

Efficient Coding : Learn to write cleaner and more efficient code by adopting the Tidyverse collection of packages designed for data science.

Data Visualization : Improve your data visualization skills with ggplot2 , focusing on creating comprehensive and attractive visual representations of your data.

Advanced Statistical Analysis : Enhance your statistical analysis skills with relevant packages. Start by mastering R packages dedicated to statistical tests.

Bioconductor for Genomics : If your research is in genomics, familiarize yourself with Bioconductor , which provides tools for the analysis and comprehension of high-throughput genomic data.

Writing R Packages : Learn to create your own R packages to streamline your workflow and share your tools with others. Hadley Wickham's book is a comprehensive guide.

Version Control with Git : Integrate your R projects with Git for version control to better manage and track changes in your code. The Happy Git and GitHub for the useR is a great resource.

Stay Updated : The R landscape is always evolving. Follow R-bloggers and join the RStudio Community to stay informed about the latest trends and packages.

Practice : Engage with real-world datasets and challenges on platforms like Kaggle to apply your skills and learn from the community.

Networking : Join R user groups or forums, attend workshops/conferences like useR! to connect with other professionals and learn from their experiences.

Focusing on these areas and leveraging the linked resources will significantly improve your R skills, making your research more efficient and impactful.

How to Display R Skills on Your Resume

How to Display R Skills on Your Resume

MATLAB is a high-level programming and numerical computing environment used by research scientists for data analysis, algorithm development, and visualization.

MATLAB is important for Research Scientists because it provides a powerful and versatile environment for numerical computation, data analysis, and visualization, enabling efficient exploration, interpretation, and presentation of scientific data and results.

How to Improve MATLAB Skills

Improving your MATLAB skills as a Research Scientist involves understanding advanced functionalities, optimizing code, and leveraging external resources. Here are concise steps with resources to enhance your MATLAB proficiency:

Master Advanced Features : Dive deeper into MATLAB's advanced features like parallel computing, machine learning, and advanced plotting. MATLAB's official documentation is an excellent place to start.

Code Optimization : Learn to write efficient, faster-running code. MATLAB's code optimization guide provides insights into improving performance.

Use Toolboxes : Explore and integrate toolboxes relevant to your research domain. Overview available at MATLAB Toolboxes .

Community and Support : Engage with MATLAB's community for code examples, troubleshooting, and new ideas. Visit MATLAB Central .

Online Courses and Tutorials : Enroll in courses or watch tutorials to enhance your skill set. Coursera and MathWorks offer MATLAB courses .

Automate Routine Tasks : Learn to automate repetitive tasks with scripts and functions to save time. Refer to this guide on writing scripts and functions .

Version Control : Use version control systems like Git with MATLAB for better management of your code versions. MATLAB's guide on using Git is helpful.

Stay Updated : MATLAB is constantly updated. Keep abreast of the latest features and functions What's New in MATLAB .

By focusing on these areas and leveraging the provided resources, you can significantly improve your MATLAB skills, leading to more efficient and effective research outcomes.

How to Display MATLAB Skills on Your Resume

How to Display MATLAB Skills on Your Resume

SPSS (Statistical Package for the Social Sciences) is a software used for statistical analysis, data management, and data documentation, widely utilized by research scientists for analyzing complex data sets and deriving insights from statistical modeling and research findings.

SPSS is vital for a Research Scientist as it provides comprehensive tools for statistical analysis, data management, and visualization, enabling efficient data interpretation and decision-making in research.

How to Improve SPSS Skills

To improve proficiency in SPSS as a Research Scientist, follow these short and concise strategies:

Enhance Statistical Knowledge : A strong foundation in statistics is crucial. Resources like Khan Academy offer excellent tutorials.

Utilize Official SPSS Tutorials : IBM provides SPSS Tutorials that cover basics to advanced techniques.

Participate in Online Forums : Engage with communities on platforms like ResearchGate or the SPSS Community to exchange knowledge and solutions.

Practice Regularly : Apply your skills on datasets related to your field. Datasets are available from sources like the UCI Machine Learning Repository .

Enroll in Workshops and Webinars : Continuous learning through structured courses or workshops, for example, those offered by Coursera or LinkedIn Learning .

Explore Advanced Features : Familiarize yourself with SPSS Syntax and the Python integration for automation and advanced analyses.

Seek Feedback : Present your findings and methodologies in forums or to peers to gain constructive feedback and new perspectives.

Incorporating these strategies will significantly enhance your SPSS skills and ensure you remain up-to-date with the latest statistical analysis techniques.

How to Display SPSS Skills on Your Resume

How to Display SPSS Skills on Your Resume

5. Machine Learning

Machine Learning is a subset of artificial intelligence that enables systems to automatically learn and improve from experience without being explicitly programmed, focusing on the development of algorithms that can analyze and make predictions or decisions based on data.

Machine learning is important for a Research Scientist because it enables the automated extraction of patterns and insights from vast amounts of data, facilitating groundbreaking discoveries and the development of innovative solutions across various scientific domains.

How to Improve Machine Learning Skills

Improving machine learning involves a combination of enhancing data quality, selecting appropriate algorithms, tuning model parameters, and continuously evaluating model performance. Here's a concise guide:

Enhance Data Quality : More data isn't always better; better data is. Focus on cleaning, preprocessing, and ensuring a diverse, representative dataset. Explore techniques for handling imbalanced data, missing values, and noise reduction. Data Preprocessing Techniques

Feature Engineering and Selection : Select the most informative features and consider engineering new features that can help improve model performance. This step is crucial for reducing complexity and improving the interpretability of the model. Feature Engineering and Selection: A Practical Approach

Algorithm Selection and Hyperparameter Tuning : Choose the right algorithm based on your problem type (e.g., classification, regression) and complexity. Use techniques like grid search, random search, or Bayesian optimization for hyperparameter tuning to find the optimal settings for your model. Hyperparameter Tuning in Machine Learning

Model Evaluation and Validation : Employ robust evaluation metrics and validation techniques (like cross-validation) to assess your model's performance. It's crucial to evaluate your model on unseen data to check for overfitting or underfitting. Model Evaluation Strategies

Ensemble Methods and Transfer Learning : Consider using ensemble methods to combine multiple models for improved performance. Transfer learning can also be a powerful technique, especially when you have limited data for training. Ensemble Learning

Continuous Learning and Experimentation : Machine Learning is an iterative process. Continuously experiment with new data, algorithms, and feature engineering techniques. Keep abreast of the latest research and advancements in the field. ArXiv is a great resource for staying updated with the latest preprints and findings in machine learning research.

By focusing on these areas, research scientists can systematically improve their machine learning models, leading to more accurate predictions, insights, and decision-making capabilities in various applications.

How to Display Machine Learning Skills on Your Resume

How to Display Machine Learning Skills on Your Resume

6. Data Visualization

Data Visualization is the graphical representation of information and data, enabling Research Scientists to see analytics presented visually, to identify patterns, trends, and outliers in data.

Data visualization is crucial for a Research Scientist as it enables the efficient communication of complex data insights and trends in a clear, engaging, and easily understandable manner, facilitating informed decision-making and hypothesis generation.

How to Improve Data Visualization Skills

Improving data visualization involves a combination of design principles, appropriate tool selection, and understanding the data's story. As a Research Scientist, focus on clarity, simplicity, and relevance:

Know Your Audience : Tailor your visualization to the audience's expertise and needs. Storytelling with Data provides insights on engaging your audience effectively.

Choose the Right Chart Type : Match the chart with the data's story. Bar charts for comparisons, line charts for trends, etc. From Data to Viz guides on choosing the correct visualization type.

Simplify : Avoid clutter. Use minimal text, remove unnecessary ticks, and legends only when needed. Edward Tufte's principles on data-ink ratio can be pivotal.

Use Color Wisely : Use color to highlight important data points or differentiate data sets, but keep the palette limited and accessible. ColorBrewer offers color advice for maps and charts.

Tell a Story : Make the data narrative engaging and clear. Nathan Yau's FlowingData provides excellent examples of storytelling with data.

Iterate and Get Feedback : Share drafts with peers for insights on clarity and impact. Iteration helps refine and simplify the visualization.

Leverage Tools and Libraries : Use tools like Tableau, Python libraries (matplotlib, seaborn, Plotly), or R packages (ggplot2) to create professional visuals. Continuous learning through resources like DataCamp for hands-on tutorials can enhance your visualization skills.

By focusing on these areas, you can significantly improve your data visualization skills, making your research findings more accessible and impactful.

How to Display Data Visualization Skills on Your Resume

How to Display Data Visualization Skills on Your Resume

7. Bioinformatics (if relevant)

Bioinformatics is the application of computational techniques to analyze and interpret biological data, enabling research scientists to understand biological processes, discover new genes, understand evolutionary relationships, and identify potential targets for drug discovery.

Bioinformatics is crucial for a Research Scientist because it enables the analysis, interpretation, and application of vast biological data sets, facilitating discoveries in genetics, molecular biology, and disease mechanisms, thereby accelerating scientific research and innovation.

How to Improve Bioinformatics (if relevant) Skills

Improving bioinformatics, especially for a Research Scientist, involves staying abreast of the latest computational tools, continuously developing programming skills, and actively participating in collaborative projects. Here's a concise guide:

Stay Updated with Latest Tools and Databases : Regularly explore and incorporate the latest bioinformatics tools and databases into your research. Resources like NCBI , EMBL-EBI , and Bioconductor provide a wealth of data and tools.

Enhance Programming Skills : Improve your proficiency in languages commonly used in bioinformatics such as Python, R, and Perl. Websites like Codecademy and Coursera offer courses tailored to these languages.

Participate in Open Source Projects and Collaborations : Engaging with the bioinformatics community through open-source projects can enhance your skills and knowledge. Platforms like GitHub host numerous bioinformatics projects seeking contributions.

Attend Workshops and Conferences : Participate in bioinformatics workshops and conferences to learn about cutting-edge research and network with other professionals. Organizations like ISCB organize events that can be very enriching.

Publish and Peer Review : Actively publish your research and participate in the peer review process. This not only contributes to the scientific community but also keeps you engaged with current research trends and methodologies.

Continuous Learning : The field of bioinformatics is rapidly evolving. Enroll in advanced courses or obtain certifications in specialized areas through platforms like edX and FutureLearn .

By following these strategies, a Research Scientist can significantly improve their expertise and contributions to the field of bioinformatics.

How to Display Bioinformatics (if relevant) Skills on Your Resume

How to Display Bioinformatics (if relevant) Skills on Your Resume

8. Statistical Analysis

Statistical analysis is the process of collecting, examining, interpreting, and presenting numerical data to discover underlying patterns and trends, enabling research scientists to validate hypotheses, identify correlations, and make informed decisions based on empirical evidence.

Statistical analysis is crucial for a Research Scientist as it provides a rigorous framework for making inferences from data, enabling the validation of hypotheses, the discovery of patterns, and the formulation of reliable conclusions, thereby ensuring the scientific integrity and reproducibility of research findings.

How to Improve Statistical Analysis Skills

Improving statistical analysis, especially for a Research Scientist, involves continuously enhancing methodology, understanding data, and applying appropriate statistical techniques. Here are concise steps with resources for deep dives:

Strengthen Statistical Foundations : Enhance your understanding of statistical principles. Resources like Khan Academy offer comprehensive lessons on statistics and probability.

Master Statistical Software : Gain proficiency in software like R, Python, or SAS. DataCamp provides specialized courses for learning these tools.

Stay Updated with Literature : Regularly read statistical journals and articles. Websites like arXiv and JSTOR can be valuable.

Understand Your Data : Knowing your data deeply aids in selecting the correct statistical tests. Guidelines on data understanding can be found through Towards Data Science.

Choose Appropriate Tests : Match your research questions with suitable statistical tests. Laerd Statistics offers guides on choosing and implementing tests.

Learn from Peer Reviews : Peer feedback can pinpoint methodological weaknesses. Engage with communities on platforms like ResearchGate.

Practice Reproducible Research : Ensure your analysis is reproducible, enhancing its reliability. The Center for Open Science provides tools and practices for reproducible research.

Continuous Learning : Enroll in MOOCs and workshops for advanced statistical methods. Coursera and edX offer courses from top universities worldwide.

By following these steps and leveraging the provided resources, research scientists can significantly improve their statistical analysis skills, leading to more robust and impactful research findings.

How to Display Statistical Analysis Skills on Your Resume

How to Display Statistical Analysis Skills on Your Resume

9. TensorFlow

TensorFlow is an open-source machine learning framework developed by Google, designed to facilitate the development, training, and deployment of deep learning models across various platforms and devices. It provides a comprehensive, flexible ecosystem of tools, libraries, and community resources that allow researchers to push the state-of-the-art in ML and developers to easily build and deploy ML powered applications.

TensorFlow is important for a Research Scientist because it provides a comprehensive, flexible ecosystem of tools, libraries, and community resources that enable the easy development, training, and deployment of machine learning models, facilitating cutting-edge research into complex algorithms and computational problems.

How to Improve TensorFlow Skills

Improving TensorFlow involves optimizing performance, enhancing usability, and expanding the toolkit's capabilities to meet the evolving needs of research scientists. Here are concise strategies:

Performance Optimization : Focus on reducing computational overhead and memory usage. Utilize TensorFlow Profiler ( TensorFlow Profiler ) to identify bottlenecks and adopt mixed precision training ( Mixed Precision ) to accelerate computations on compatible hardware.

Usability Enhancement : Simplify the API and improve documentation to make TensorFlow more accessible. Encourage community contributions to TensorFlow's GitHub ( GitHub TensorFlow ) for a diverse range of use-case examples and troubleshooting documentation.

Capability Expansion : Integrate the latest AI and machine learning research by regularly updating TensorFlow with new algorithms, layers, and model architectures. Stay abreast of current research through arXiv ( arXiv ) and implement cutting-edge techniques into TensorFlow.

Collaboration and Community Building : Foster a vibrant community by organizing TensorFlow meetups, workshops, and hackathons. Engage with the TensorFlow community on forums ( TensorFlow Forum ) to share knowledge, gather feedback, and collaborate on projects.

Customization and Flexibility : Enhance TensorFlow's custom operation capabilities, making it easier for researchers to implement novel algorithms without significant overhead. TensorFlow Custom Ops ( Custom Ops ) guide provides a starting point.

By focusing on these areas, TensorFlow can be improved to better serve the needs of research scientists, facilitating more efficient and innovative research in the field of machine learning.

How to Display TensorFlow Skills on Your Resume

How to Display TensorFlow Skills on Your Resume

10. Quantum Computing (if relevant)

Quantum computing is a type of computing that leverages the principles of quantum mechanics to process information. Unlike classical computing, which uses binary bits (0s and 1s) for processing, quantum computing uses quantum bits or qubits. Qubits can exist in multiple states simultaneously (a property known as superposition) and can be entangled with other qubits, allowing quantum computers to perform complex calculations more efficiently than classical computers for certain tasks. This technology has potential applications in fields such as cryptography, drug discovery, optimization problems, and more.

Quantum computing is important for research scientists because it offers unprecedented computational power to solve complex problems in fields such as cryptography, materials science, and pharmaceutical development that are intractable for classical computers, potentially leading to groundbreaking discoveries and innovations.

How to Improve Quantum Computing (if relevant) Skills

Improving quantum computing involves enhancing the stability, scalability, and efficiency of quantum systems. Here are concise strategies tailored for a Research Scientist:

Enhancing Qubit Quality : Focus on developing high-coherence qubits to reduce error rates. Investigate materials and designs that prolong qubit coherence times. Explore superconducting qubits and topological qubits for their potential in error resistance.

Error Correction : Implement advanced quantum error correction codes to mitigate errors without significantly increasing the overhead. Research on surface codes and topological error correction offers promising paths. Delve into quantum error correction techniques .

Quantum Software and Algorithms : Develop algorithms that can run efficiently on near-term quantum devices. Investigate hybrid quantum-classical algorithms and optimizations for specific quantum architectures. The Quantum Algorithm Zoo is a comprehensive resource.

Scalability Solutions : Address physical and engineering challenges to scale up quantum systems while maintaining operation fidelity. Research on modular quantum computing and photonic approaches can provide insights. The scalability of quantum computing offers a detailed discussion.

Quantum Simulation : Use quantum computers to simulate complex quantum systems, providing insights into materials science, chemistry, and physics. This involves developing efficient simulation algorithms. The quantum simulation research is pivotal.

Cryogenic Electronics : Since many quantum computers operate at cryogenic temperatures, improving cryogenic control electronics can enhance performance and reduce heat load. Explore advancements in cryogenic electronics for quantum computing.

Quantum Communication and Networking : Work on quantum communication protocols and quantum repeaters to enable secure quantum networks. This includes research on quantum key distribution (QKD) and entanglement distribution. Quantum networking provides insights into current developments.

By focusing on these areas, research scientists can contribute to overcoming the current limitations and unlocking the full potential of quantum computing.

How to Display Quantum Computing (if relevant) Skills on Your Resume

How to Display Quantum Computing (if relevant) Skills on Your Resume

11. CRISPR (if relevant)

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a revolutionary gene-editing technology that allows for precise, targeted modification of the DNA in living organisms, widely used in genetic research and biotechnology.

CRISPR is a revolutionary gene-editing tool that allows for precise, efficient, and relatively easy modification of DNA in living organisms, enabling groundbreaking advancements in genetics research, disease treatment, and biotechnology.

How to Improve CRISPR (if relevant) Skills

Improving CRISPR involves enhancing its accuracy, efficiency, and specificity. Here are concise strategies:

Cas Protein Engineering : Modifying Cas proteins to reduce off-target effects. For example, engineered variants of Cas9, like eSpCas9 and HypaCas9, show improved specificity ( Nature Biotechnology, 2016 ; Nature Communications, 2018).

Guide RNA (gRNA) Optimization : Designing gRNAs with reduced off-target activity and increased on-target activity. Tools like CRISPRscan can be used for more effective gRNA design ( Nature Methods, 2015 ).

Use of Anti-CRISPR Proteins : These proteins can inhibit CRISPR-Cas9 activity, providing a method to control gene editing temporally and reduce off-target effects ( Nature, 2017 ).

Prime Editing : A newer, more precise form of CRISPR editing that doesn't rely on double-strand breaks, reducing the risk of unintended mutations ( Nature, 2019 ).

Chemical Modifications : Modifying the ribose-phosphate backbone of gRNAs can improve stability and reduce off-target effects ( Nature Biotechnology, 2017 ).

CRISPR Base Editing : Directly converting one DNA base pair to another without double-strand breaks, offering high precision editing ( Nature, 2016 ).

Each of these strategies can be tailored to specific research goals, enhancing the power and precision of CRISPR technology in genome editing.

How to Display CRISPR (if relevant) Skills on Your Resume

How to Display CRISPR (if relevant) Skills on Your Resume

HPLC, or High Performance Liquid Chromatography, is a highly precise analytical technique used to separate, identify, and quantify components in a mixture, based on their interactions with a stationary phase and a mobile phase under high pressure.

HPLC (High-Performance Liquid Chromatography) is crucial for a Research Scientist as it allows for the precise separation, identification, and quantification of compounds in complex mixtures, facilitating the analysis of reaction products, impurities, and active pharmaceutical ingredients with high sensitivity and accuracy.

How to Improve HPLC Skills

Improving High-Performance Liquid Chromatography (HPLC) performance involves optimizing several parameters to enhance efficiency, resolution, and sensitivity. Here are concise strategies:

Column Choice : Select the appropriate column material, size, and particle size for your analyte. Smaller particles increase resolution but require higher pressure. Choosing Columns for HPLC Method Development.

Mobile Phase Optimization : Fine-tune the solvent composition, pH, and ionic strength to improve peak shape and separation. Gradient elution can be more effective for complex mixtures. Optimizing Mobile Phase Conditions for Reversed-Phase HPLC.

Temperature Control : Adjusting the column temperature can enhance separations and reduce viscosity, leading to lower backpressure and faster runs. The Role of Temperature in Liquid Chromatography.

Flow Rate Adjustment : Modify the flow rate to balance between analysis time and resolution. Faster flow rates decrease analysis time but may reduce resolution. Impact of Flow Rate on HPLC Separations.

Sample Preparation : Proper sample preparation can reduce matrix effects, improve peak shape, and increase sensitivity. Consider solid-phase extraction or dilution as needed. Sample Preparation Techniques for Better Chromatographic Analysis .

Detector Optimization : Choose the most suitable detector based on the analyte's properties. Adjusting detector settings like wavelength (for UV detectors) can significantly enhance sensitivity. Guide to Choosing and Using HPLC Detectors.

Regular Maintenance : Routine maintenance of the HPLC system, including cleaning and replacing worn parts, prevents unexpected issues and ensures consistent performance. Maintaining Your HPLC System.

By systematically addressing these aspects, you can significantly improve the performance of your HPLC analyses.

How to Display HPLC Skills on Your Resume

How to Display HPLC Skills on Your Resume

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Research Scientist

  • Research Scientist

How to Become a Research Scientist

  • Career Types
  • Work Environment
  • How to become
  • Skills and Traits
  • Certifications/Internship
  • Career Progression

Who is a Research Scientist?

Everything that you see around you has been invented or discovered by the work of some extraordinary individuals who are known as research scientists. These individuals are responsible for carrying out scientific activities and are involved in the study of the world around them. They are also dedicated to improving the quality of life on the planet by developing new scientific methods and techniques.

If you are a science enthusiast who has a passion for the subject and is interested in learning more about the world around you, then you should consider becoming a research scientist. In addition to being involved in scientific activities, research scientists also have the opportunity to earn a living. In this article, we will be discussing how to become research scientist after 12th or how to become a research scientist in India. 

Research Scientist

Research Scientist in a Nutshell

The passion for finding answers and the excitement of working on projects are some of the factors that make a fascinating research scientist career. However, working on a project can also expose them to various challenges and failures. A research scientist's job involves a wide variety of subjects and tasks.

Quick Facts for Research Scientist

Male, Female

Research scientist jobs are suitable for individuals who are interested in becoming a part of the technology and science industry. Both men and women can pursue this research scientist career. The right attitude and skills are some of the factors that a person should consider when it comes to choosing a research scientist career in this field.

Individuals with strong analytical and critical thinking skills can become a research scientist. There are no restrictions to this type of job, and it can be done remotely. In addition, there are various fields of science that can be done without any external efforts or physical movement. This is a perfect job for people with special needs.

Table of Contents for Research Scientist

What is the role of research scientist.

A research scientist is a person who is responsible for managing various tasks and projects, such as teams, documents, and projects. Some of them are from scratch, while others require some form of intermediary involvement. As a research scientist, you will be categorised into two categories: experimental and theoretical.

An experimental research scientist is a scientist who carries out the experiments and test results of a project. On the other hand, a theoretical research scientist is a scientist who works on the concepts and equations of a project.

The duties of a research scientist include overseeing the availability of the necessary services and equipment within the company at all times. He or she is also responsible for ensuring that the organization's policies and procedures are followed. The ideal candidate for this job would have the necessary skills and knowledge to maximize the efficiency of the company's resources.

Supervision

The duties of a research scientist include ensuring that the needs of the studies and trials are met at the centre of the care delivery process. He or she is also responsible for ensuring that the environment is safe and that the equipment used for the studies is working properly.

Team management

As a research scientist, he or she is responsible for ensuring that the various tasks and projects are carried out in a way that is consistent with the goals and objectives of the project. He or she is also expected to ensure that the team members come up with the best possible approach to the project.

Leadership Skills

Research scientists are expected to provide effective leadership and promote sound scientific practices. They are also responsible for developing support mechanisms that encourage and guide innovation in the field.

Maintenance work

As a research scientist, you will be responsible for disseminating knowledge and skills to other disciplines within the company. You will also be expected to deal with government officials and other organizations in stressful situations.

Research work

In certain situations, a research scientist's job involves carrying out a local audit and conducting research to ensure that the findings are properly disseminated. This type of work is usually carried out in order to obtain approval from the ethical council.

Types of a Research Scientist

There are various types of research scientists working in different scientific fields. These associates are responsible for analysing and disseminating scientific information.

Astronomer :  Astronomers are responsible for studying stars, galaxies, and planets. They also track the non-celestial objects in outer space. This field involves working closely with other scientists to study planetary movements.

Botanist :  As a botanist, one of the main roles of this field is to study the various aspects of the plants that are commonly found in the environment. They analyse the plant's structure, development, and uses.

Geologist :  As a Geologist, one of the most important roles in this field is to study the various elements of the Earth, including its solid, liquid, and gaseous state. He or she also studies the history and evolution of the planet.

Marine Biologist:  As a marine biologist, one of the main areas of specialisation is the study of the various marine organisms that live in the environment. This field involves analysing the interactions between plants and animals. After gaining a broad understanding of oceanography and biological oceanography, marine biologists conduct close research on different aquatic species.

What is the workplace/work environment of Research Scientist like?

As a research scientist, you will be part of a team working in different areas of the research, such as medical centres and laboratories. You will be expected to keep up with the latest developments in the field and the theoretical and experimental history of the project.

Does Research Scientist require travelling?

One of the main advantages of being a research scientist is that you will be working in a single research area, and you will typically spend about 90 per cent of your time in the OR suite. In other cases, you will be expected to work in different areas of the research, such as laboratories and experimental fields.

Employment Shifts

Full time, part time.

Research scientists are typically expected to work up to 60 hours per week, and they may also be required to be present on call during certain hours of the day. In certain facilities, where there are numerous trials, research scientists may be required to work in shifts to ensure that there are trained staff members available 24 hours a day.

Employment Nature

The nature of a research scientist's work is that it is a permanent position, which means that employers can hire them on a permanent basis. Medical centres and other third-party companies often hire research scientists.

As a research scientist, you will be expected to work in different areas of research, such as medical centres and laboratories. You will be expected to keep up with the latest developments in the field and the theoretical and experimental history of the project.

Presence in Geographical Area

Semi-urban, urban.

Tier-1 cities such as New Delhi, Bengaluru, Hyderabad, and Kolkata are known for their healthcare facilities and are known to be great places for research workers. In Tamil Nadu, the average research scientist salary is 10.6 per cent higher than the national average. In Bangalore and Karnataka, the research scientists earn more than the national average, while in Mumbai, the lowest pay is around 11.5 per cent.

Time Pressure

As a research scientist, you will be expected to work from 9 am to 5 pm, and you may be required to perform various shifts depending on the schedule.

Overtime Details

Research scientists are expected to work overtime, and this is typically done under certain circumstances. Apart from working long hours, they are also expected to perform other tasks that involve weekends and long days.

Weekly Hours of Work

Min 45 hours.

In certain facilities, where there are numerous trials, research scientists may be required to work in shifts to ensure that there are trained staff members available 24 hours a day.

How to become a Research Scientist?

Steps to become a research scientist.

If you are someone who enjoys doing research or want to know things in-depth then a career as a Research Scientist is the most suitable career for you. If you are looking for the details of how to become a research scientist in India or how to become a research scientist after 12th then you have come to the right place. We have mentioned below the steps for how to become a Research Scientist in India. 

Identify Skills

Enrol in formal training/course, pursue a specialised certification, build an attractive resume, gain experience, find a suitable job, begin a career.

To become a Research Scientist you are required to know what skills are required for a career as a Research Scientist. We have mentioned below some of the soft skills and hard skills.

Some of the soft skills for how to become a Research Scientist in India are attention to detail, communication skills, analytical skills, time management, collaboration and creativity. 

Creativity 

Curiosity 

Communication

Productivity

Formulaic Thinking 

Apart from that, you must also have some of the hard skills that are required to become a Research Scientist in India are cell culture, biochemistry, and data analysis. 

Data Analysis

Data Collection

Research Projects

Molecular Biology

Python and Java 

Cell Culture 

Experimental Design

If you are still looking for how to become a Research Scientist in India, then the most essential step for you to take is that you must opt for a formal training programme to gain knowledge in the subject and to opt for a career as a Research Scientist. You are required to complete 10+2 in Biology , Chemistry , Physics , and Mathematics from a recognised board in India. 

After you have completed your 10+2, you must opt for a bachelor’s degree by appearing for the entrance examination and then opt for a master’s degree in MSc Clinical Research or any other related degree. Below, We have mentioned the Research Scientist entrance examination, bachelor’s and master’s degrees.

Entrance Examinations

Bachelor’s Degree Programmes

Master’s Degree Programmes

If you are looking for how to become a Research Scientist in India, then you can also opt for a specialised certification. If you pursue a certification course you will gain more knowledge and skills. Below we have given some of the specialised certifications. 

Once you have completed your formal degree and certifications, you are required to create an attractive resume with all of your details such as subject knowledge and skills, your interest in the research field, and your educational background. Your resume must be in a formal and professional tone.

If you want to develop your skills and knowledge practically and gain industry experience then you must pursue an internship. Before you pursue your Ph.D. program it is better that you work for one to two years. You can upload your resume to various internship platforms, or connect directly to popular laboratories and research centers where you can work under the supervision of experienced professionals.

Once you have completed your training or internship, you can now apply for full-time job opportunities. You can apply on various job offering platforms such as Naukri, Linkedin, Monster and Indeed. Apart from that you can also approach directly to some of the laboratories or research institutes or universities. 

This is the final step in how to become a Research Scientist in India. After attending some of the related interviews you can select the best and the right offer and accept it and join the company and begin your career. 

What are the skills and qualities required to become a/an Research Scientist?

  • Communication skills
  • Critical thinking
  • Learning Skills
  • Attention to detail
  • Physical strength
  • Science skills

Patience:  As a research scientist, one has to remain calm and make the right decisions in order to carry out their duties. This is very important in order to maintain the continued success of the research project. The work that the associate does helps in developing new methodologies for human life.

Physical Strength: Having the proper physical strength and mental focus is very important for a research scientist to be successful in their job. Besides being physically fit, research scientist also needs to stay focused and alert during their trials, which can last for up to 8 hours.

Communication Skills:  One of the most critical skills that research scientists need to develop is communication skills. This is because, in a high-stakes environment, communicating effectively is very important.

Science Skills: People should have a deep understanding of science in order to excel in their field. This is very important for them to become a research scientist. Besides being able to excel in the field, it is also very important that they have a passion for technology.

Attention to Detail: One of the most important factors that a research scientist should consider when it comes to becoming a research scientist is the importance of paying attention to detail. This is because, in order to produce the best possible work, one must always be able to make the necessary decisions.

Critical Thinking:  As a research scientist, you must have the necessary skills to analyse and interpret data in order to make informed decisions. This discipline involves identifying the weaknesses and strengths of various solutions. Besides being able to analyse and interpret data, a research scientist also needs to have the necessary analytical skills to deal with difficult situations.

Learning Skills: In addition to being able to analyse and interpret data, a research scientist also needs to have the necessary analytical skills to deal with difficult situations. Learning skills are very important in a career as a research scientist. This discipline involves conducting various tasks such as inspecting and testing equipment.

Which certifications and internships can be helpful in becoming Research Scientist?

Individuals aspiring to become research scientist can upgrade their skills by taking various certification courses. These courses can help them perform at their best.

Internship Availability

Several organisations in the science and technology industry provide internships to students. These are designed to provide them with an opportunity to enhance their technical skills and experience, as well as learn more about becoming a research scientist. To apply, students must go through the website portals of their choice. They are also required to provide their CV and meet the requirements of the internship. Shortlisted candidates will be given various opportunities throughout the year.

Career Path Progression for Research Scientist

Junior Research Scientist:  Junior research scientists are responsible for providing technical guidance to the technicians and interns working in other fields who are under their expertise. These individuals use their knowledge in the areas they work in to improve their efficiency.

Senior Research Scientist:  A senior research scientist is a person who focuses on the principles of various engineering disciplines such as electrical, chemical, and physics. They supervise the technicians and technologists who are involved in the production or research of the project. They also prepare reports and perform other tasks to communicate engineering recommendations.

Research Scientist Jobs and Salaries

Junior research scientist.

  • Average Salary 39000

Job Description

The Junior Research Scientist job description includes planning and conducting experiments, and formulating and executing investigative protocols. A Junior Research Scientist does data collection and analysis. 

Salary Description

An entry-level Junior Research Scientist salary in India ranges between Rs 2.0 Lakhs to Rs 9.8 Lakhs with an average annual salary of Rs 5.0 Lakhs per annum. Junior Research Scientist in India may vary depending on the various job factors like the skills and experience of the candidates, job location, and others.

Salary Source: AmbitionBox

Senior Research Scientist

  • Average Salary 70000

The Senior Research Scientist job description includes securing the funding, publishing the findings and conducting in-house research presentations. A Senior Research Scientist promotes beneficence, minimises risks, and collects and analyses data.

The estimated Senior Research Scientist salary in India ranges from Rs 5.6 Lakhs to Rs 20.0 Lakhs with an average annual salary of Rs 10.0 Lakhs per annum. Senior Research Scientist salary may vary depending on the various job factors.

What is the job outlook for Research Scientist?

There are numerous growth opportunities in a research scientist career. You can choose to specialise in one of the areas of corporate social responsibility or develop new skills in areas such as research and development.

One of the oldest research scientist career in the industry, research scientist has plenty of scope and potential. In addition to being in the medical and biological sectors, research scientist jobs are also available in engineering technology fields. This field is heavily influenced by the discoveries made in the field of engineering, which involves the study of particulate matter.

Frequently Asked Questions for Research Scientist

Que. how to become a research scientist in biotechnology.

You must pursue a bachelor's degree by giving an entrance exam like ARS NET, JRF,  ICMR, and DBT NET and opt for a master's degree in MSc Biotechnology and must opt for an internship for atleast one to two years.  

Que. How to become a research scientist in physics?

You must pursue a bachelor's degree by giving an entrance exam like JEST, or UGC-NET and opt for a master's degree in biochemistry, biology, or pharmacology and must opt for an internship for atleast one to two years.  

Que. How to become a research scientist in biology?

You must pursue a bachelor's degree in biology by giving an entrance exam and opt for a master's degree in biochemistry, biology, or pharmacology and must opt for an internship for atleast one to two years. After that, you can opt for a PhD.

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Interview questions related to b.com.

Dear Aspirant !

Hope you are doing well !

These questions can be asked which are as follows;-

  • What are liquid assets? ...
  • What is the purpose of audits? ...
  • What is a value-added tax? ...
  • What is a capital asset? ...
  • What is a subsidy? ...
  • What is the role of a public relations department? ...
  • What do you understand about equilibrium? ...
  • What is a futures market?.

Hope it helps you!

which is the best MSc in microbiology or MSc in bio physics?in terms of jobs as a research scientist after completing my bsc degree in microbiology ...

Hello Aspirant,

There are numerous opportunities ahead for graduates of M.Sc Microbiology. The scope has risen for M.Sc. microbiology graduates with the emergence of COVID. The demand for researchers has constantly increased to determine whether its existence in the human ecosystem is natural or man-made.

An M.Sc. in microbiology provides numerous opportunities in various fields such as education, healthcare, pharmaceutical, and agriculture.

Graduates can find career opportunities in both the private as well as public sectors. The agriculture sector also demands skilled professionals for microbiological research on subjects like rhizosphere, nitrogen fixation, biogas production, soil enzymes, and anaerobic decomposition.

Further, you can know more about the top colleges, salary packages, etc at https://www.careers360.com/courses/msc-in-microbiology#:~:text=Benefits%20of%20Studying%20M.Sc%20Microbiology%20A%20M.Sc.%20in,both%20the%20private%20as%20well%20as%20public%20s

MSc Biophysics: Biophysics is an advanced field of science that uses the techniques of physical science to study biological systems.

Benefits of studying biophysics:

1. Biophysicists can also work in universities, industry, medical centers, research institutes, and government.

2. Candidates can find jobs as biophysics researchers or scientists with research institutes or government organizations in various academic grades for research-oriented programs.

3. The course is beneficial for those who are curious about biological processes and enjoy puzzle solving, designing experiments, or working with numbers and computers, there are many exciting opportunities for you in biophysics.

4. They can even find a job as a professor or member of faculty in a university, medical or dental college offering a program in biophysics.

Further, You can know about this course at https://www.careers360.com/courses/bio-physics-course

In the end, what matters the most is in which area your interest lies and the amount of hard work you put into it.

Best Wishes!

I wanted to ask that do research scientist ( I mean kvpy scholar) earn good amount of money in India ?

Dear aspirant,

Department of Science and Technology, Government of India has started Kishore Vaigyanik Protsahan Yojana or Young Scientist Incentive Plan for encouraging young scientists in pursuing research career courses in basis sciences upto Pre-Ph.D level.

The KVPY students receive a amout of Rs. 5000 monthly fellowship from first year of degree to final year of degree in courses like Integrated M.S or M.Sc, B.Sc or B. Statistics or B. Mathematics or B.S Maths/ Integrated M.S./M.Sc. They receive amount of Rs. 20,000 per year as annual contingency grant. After 3 years the amount is increased to Rs. 7000 and annual grant of Rs. 28,000 is given.

Candidates can also get DST Inspire Scholarship with worth of Rs. 80,000 per annum. The scholarship is given on the basis of Skill test conducted every year.

I hope this information was useful to you.

Best of Luck!!

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RESEARCH SCIENTIST

Durham, NC, US, 27710

School of Medicine

Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental scientific discoveries to improve human health locally and around the globe. Composed of more than 2,600 faculty physicians and researchers, nearly 2,000 students, and more than 6,200 staff, the Duke University School of Medicine along with the Duke University School of Nursing, and Duke University Health System comprise Duke Health, a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations.

Occ Summary

A Research Scientist position is available in the Department of Neurosurgery at Duke University. The position will also aid the overall research program spanning bench to bedside with a multidisciplinary team within surgery, radiation oncology, medical oncology, and palliative care. Key features of this role include (1) coordination, growth and development of the program’s translational research portfolio, (2) grant writing assistance for local, federal and/or foundation grants pertinent to the program, and (3) oversight of clinically-annotated banked tissues from patient samples treated at Duke for brain and spine metastases.

We are seeking motivated individuals to investigate the mechanisms of metastatic progression to the bone and spine. The successful candidate will work in a collaborative environment with other scientists in the Departments of Neurosurgery. This position will specifically 1) investigate the genetic and epigenetic alterations associated with primary and metastatic spine and bone disease, 2) characterize tumor-specific, tumor microenvironment associated changes and immune cell changes in hormone-responsive cancers using molecular approaches with the goal of characterizing novel biomarkers and signatures associated with metastatic spine disease 3) investigating pre-clinical models of novel therapeutics.

The Research Scientist will be responsible for:

  • Performing a variety of routine molecular biology (e.g., isolation of nucleic acids, PCR, ELISAs) and microbiology techniques.
  • Maintaining mouse models (e.g., routine husbandry, genotyping, maintaining inventory), administering compounds to mice (injections, oral gavage), performing dissections to isolate and characterize organs, spines, bones, lymphocytes from various tissues, and conducting relevant animal models of disease (e.g., mammary fat pad, subcutaneous, intracardiac, tail vein, orthotopic brain and spine transgeneic and syngeneic models).
  • Assisting with planning specific research procedures across laboratory and animal facilities.
  • Carry-out literature review to guide research.
  • Perform standard technical procedures such as PCR, qPCR, and electrophoresis, etc.
  • Perform DNA extraction from human clinical specimens, fresh-frozen and/or paraffin-embedded tissue and aid in execution of experimental design and analysis of next generation sequencing data.
  • Organize and perform integrative analysis of complex genetic and morphologic data, including computational and/or statistical analysis. Developing and troubleshooting new techniques and processing samples for appropriate downstream data analysis.
  • Maintaining organized and up-to-date records of results and methodologies.
  • Compiling and helping analyze data, preparing charts, graphs, and results of studies.
  • Helping the lab run safely and efficiently, including ordering supplies, maintaining safety approvals, and managing equipment. • Establish and execute a validation/verification plan in light of biomarker discovery.
  • Aid with drafting LOI’s, (2) preparing IRB applications, (3) preparing budgets, (4) interfacing with industry or foundation partners to develop concepts, (5) submitting protocols for scientific and regulatory review, (6) helping process amendments, (7) assisting with abstract, posters, and manuscript drafts (including reference management and submission of materials).
  • Position will be involved in training and education of neurosurgery residents, medical and graduate students in the School of Medicine, and undergraduates under the leadership of the Director of Spine Oncology. 

Requirements: 

PhD (or doctoral degree equivalent) in Cancer Biology, Genetics, or Cell Biology with a track record of publication in peer-reviewed journals. Candidates with strong interest in clinical diagnostic molecular genetics, expertise in tumor biology and/or animal models of metastasis are encouraged to apply. The position entails a one- to five-year period, with extension contingent on performance and funding.   

  • Ability to perform molecular & cellular protocols and mouse models, cloning, mutagenesis, standard biochemistry for protein analysis, viral-based protocol.
  • Qualifying competencies include excellent oral and written communication skills.
  • Analytical skills to resolve complex problems requiring the use of scientific, mathematical, or technical principles and in-depth, experienced-based knowledge.
  • Experience with the care and handling of mice, flow cytometry, and molecular biology techniques is preferred.
  • Excellent organizational skills, creativity, self-motivation, ability to work independently and as part of a team. 
  • Willingness and ability to take on multiple projects simultaneously.
  • Experience in Bioinformatics is a plus·
  • Strong written and communication skills
  • Excellent interpersonal, problem-solving, communication and organizational skills.
  • Flexibility, motivation, and ability to work independently.

How to Apply: 

To apply , please e-mail a single PDF file that includes the following to [email protected] • A cover letter that describes your research and career goals, and your expertise or experience related to: a) molecular cloning OR b) post-translational regulation of protein/gene expression & function • A curriculum vitae, including a publication list with a brief (2-3 sentence) description of your contributions to published work. • Names and contact information for 3-5 references.

Work Performed

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Knowledge, Skills and Abilities

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See job description for education requirements.

Duke is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status.

Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values.

Essential Physical Job Functions: Certain jobs at Duke University and Duke University Health System may include essentialjob functions that require specific physical and/or mental abilities. Additional information and provision for requests for reasonable accommodation will be provided by each hiring department.

Nearest Major Market: Durham Nearest Secondary Market: Raleigh

Duke is an Affirmative Action / Equal Opportunity Employer committed to providing employment opportunity without regard to an individual’s age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status. Read more about Duke’s commitment to affirmative action and nondiscrimination at hr.duke.edu/eeo.

Skills and Strategies for Research and Reading

  • First Online: 03 April 2024

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  • Jacqueline S. Stephen   ORCID: orcid.org/0000-0001-8949-5895 2  

Part of the book series: Springer Texts in Education ((SPTE))

In addition to study skills and study habits, students need to be able to effectively engage in the process of research and college-level reading. Chapter 8 explains the significance of effective research and reading skills on academic performance. There are many types of research activities that college and university students are expected to actively participate in to complete various course requirements. Similarly, there are many different forms of literature that a student will encounter while engaging in the research process. College and university libraries provide access to a many of resources to support students through the research process. Thus, this chapter introduces students to the different types of research activities they can expect to engage in through their courses, explains the different forms of literature that a student may encounter during the research process, and provides insight into the many resources that libraries often provide to support student research activities and student development of college-level research skills. One of the areas of student development is in reading skills. Hence, Chapter 8 explains the various types of reading materials that a student may encounter in college or university courses, provides information on the styles of reading academic texts, and presents strategies to promote effective research and reading, including best practices for evaluating the relevancy and credibility of information sources.

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Stephen, J.S. (2024). Skills and Strategies for Research and Reading. In: Academic Success in Online Programs. Springer Texts in Education. Springer, Cham. https://doi.org/10.1007/978-3-031-54439-2_8

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By Jenna Somers

Jessica Logan

Associate Professor of Special Education Jessica Logan has always been interested in child development, specifically the growth of academic skills in young children at risk for learning disabilities. She seeks to understand how children learn and the contexts in which they learn, exploring questions such as, “Why do some kids struggle with learning to read?”

But for Logan, it’s not enough to ask a research question and then develop a methodology. The methodology itself must be studied to understand whether it is best for answering the question. As new questions arise, new statistical methods may need to be designed and implemented. Likewise, new designs may generate new questions that otherwise could not be answered.

In graduate school, Logan’s passion for developmental science spurred her passion for quantitative methodology. Now she uses her skills not only to improve her own work but to study the statistical methodologies used in her field, and to support her colleagues in developing and refining their research designs. In short, Logan is a meta-scientist on a mission.

“Metascience is really at the heart of everything I do. I study what methods researchers are using to understand questions about child development and how we can innovate and improve methods to better align with those questions. If we want to ensure the best outcomes for children, we should study problems using the methods that best address each question,” Logan said.

To support her colleagues, Logan leads workshops on best practices for data management and data sharing , and how to implement novel statistical methods to rescue research projects marred by missing data .

In a recent project supported by a $837,860 grant from the National Institutes of Health, Logan and her colleague Sara Hart , professor of psychology at Florida State University, are developing intensive short courses in data management and data sharing for researchers in children’s learning and development. Data management concerns processes for collecting, organizing, validating, and securing data. Data sharing refers to the practice of sharing research data for use by other investigators.

Logan says that roughly 80 percent of researchers in the field of children’s learning and development do not share their data, but interest in developing best practices for data sharing is growing. As part of this grant, Logan will host 20 investigators in the field of developmental science for a five-day course in data management and data sharing at Vanderbilt Peabody College of education and human development in August. Courses supported by this grant have the potential to improve data management and sharing practices in the field of children’s learning and development, which ultimately could improve the work of practitioners and outcomes for the children they serve.

Logan and Hart don’t just educate colleagues through workshops. In the early days of the COVID-19 pandemic in 2020, when physical isolation was hindering the professional growth of many early-career researchers, Logan and Hart began cohosting the podcast Within and Between . They wanted to reach a wide audience of young developmental scientists, many of whom peppered them with questions about the methods and metascience of developmental science and professional development concerns. As the tagline for the inaugural episode states, “When one person asks for advice, you give it to them. When five people ask you for advice, you start a podcast.” Through four seasons, Logan and Hart have offered advice on topics such as the open science practice of preregistering research plans publicly, developing research questions, deciding on which conferences to attend and why, preparing for annual faculty reviews, and of course, all things data management.

And when Logan, Hart, and several of their colleagues asked each other for advice on navigating systemic inequities in their field, they started POWER (Providing Opportunities for Women in Educational Research), a non-profit organization to connect, support, and advocate for researchers who identify as women or non-binary in the fields of education and child development.

“Women have held the majority of Ph.D.’s in education for a very long time—it’s a unique field in that way—but they hold fewer positions of power, so they are less likely to remain in the field. Early in their careers, researchers are postdocs and assistant professors, and female researchers who have children during this time are often held back. The tenure clock gets pushed back, but that pushes back raises and promotions, which affects their perception within their departments and their ability to contribute to science. They might get entry-level academic positions, but they occupy fewer leadership roles, are less likely to achieve tenure, and are less likely to receive federal funding than their male peers,” Logan said.

To help close the gap, POWER has a database to connect women and non-binary researchers in education and child development. The database can help users find potential research collaborators, mentors, colleagues who can write letters of support, and more.

Additionally, POWER provides a list of resources and hubs to connect researchers based on geographic locations and research specializations. The organization also hosts online and in-person networking events and has an active email listserv. Membership is free and open to any researcher in the field of education or child development.

As a researcher, podcaster, and leader of a non-profit, Logan wears many different hats, but no matter which one she wears at any given time, her mission is the same: to help improve the scholarship of education and developmental science researchers, so that their work can lead to better outcomes for children.

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Public Health Sciences Learning Objectives

Public health sciences students graduate with the knowledge and skills necessary to be successful in the workplace, public health sciences major - learning objectives.

Students in the Public Health Sciences major graduate with the following skills and abilities: 

  • Describe the concept of population health and the basic processes, approaches, and interventions specific to the needs and concerns of populations. 
  • Evaluate the source and quality of health information and data as related to individual and community health. 
  • Demonstrate mastery in public health communication skills including oral communication and written communication for both lay and expert audiences.
  • Assess the values and perspectives of diverse individuals, communities, and cultures, and describe how these factors influence health behaviors, choices, and practices. 
  • Engage in collaborative, team-based, and interdisciplinary approaches for improving population health. 
  • Identify public health tools and evidence-based strategies to respond to public health issues in a global world.
  • Gain awareness of and exposure to the broad and diverse range of areas of study within the field of public health, and identify and explore areas that are of personal interest.

The Public Health Sciences major is accredited by the Council for Education on Public Health

Courses in the Public Health Sciences major provide instruction in the following domains and competencies, developed by the Council for Education on Public Health. 

Foundational Domains

  • The concepts and applications of basic statistics 
  • The foundations of biological and life sciences 
  • The history and philosophy of public health as well as its core values, concepts, and functions across the globe and in society 
  • The basic concepts, methods, and tools of public health data collection, use, and analysis and why evidence-based approaches are an essential part of public health practice 
  • The concepts of population health, and the basic processes, approaches and interventions that identify and address the major health-related needs and concerns of populations 
  • The underlying science of human health and disease, including opportunities for promoting and protecting health across the life course 
  • The socioeconomic, behavioral, biological, environmental, and other factors that impact human health and contribute to health disparities 
  • The fundamental concepts and features of project implementation, including planning, assessment, and evaluation 
  • The fundamental characteristics and organizational structures of the U.S. health system as well as the differences between systems in other countries 
  • Basic concepts of legal, ethical, economic, and regulatory dimensions of health care and public health policy and the roles, influences, and responsibilities of the different agencies and branches of government 
  • Basic concepts of public health-specific communication, including technical and professional writing and the use of mass media and electronic technology

Foundational Competencies

  • Communicate public health information, in both oral and written forms, through a variety of media and to diverse audiences 
  • Locate, use, evaluate, and synthesize public health information

Accreditation

The Public Health Sciences major at UMass Amherst is accredited by the Council on Education for Public Health, which is an independent agency recognized by the U.S. Department of Education to accredit schools of public health, and public health programs outside schools of public health.

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Stephen Ornes

Large Language Models’ Emergent Abilities Are a Mirage

Illustration of researchers taking measurements around a head sculpture.

The original version of this story appeared in Quanta Magazine .

Two years ago, in a project called the Beyond the Imitation Game benchmark , or BIG-bench, 450 researchers compiled a list of 204 tasks designed to test the capabilities of large language models , which power chatbots like ChatGPT. On most tasks, performance improved predictably and smoothly as the models scaled up—the larger the model, the better it got. But with other tasks, the jump in ability wasn’t smooth. The performance remained near zero for a while, then performance jumped. Other studies found similar leaps in ability.

The authors described this as “breakthrough” behavior; other researchers have likened it to a phase transition in physics, like when liquid water freezes into ice. In a paper published in August 2022, researchers noted that these behaviors are not only surprising but unpredictable, and that they should inform the evolving conversations around AI safety , potential, and risk. They called the abilities “ emergent ,” a word that describes collective behaviors that only appear once a system reaches a high level of complexity.

But things may not be so simple. A new paper by a trio of researchers at Stanford University posits that the sudden appearance of these abilities is just a consequence of the way researchers measure the LLM’s performance. The abilities, they argue, are neither unpredictable nor sudden. “The transition is much more predictable than people give it credit for,” said Sanmi Koyejo , a computer scientist at Stanford and the paper’s senior author. “Strong claims of emergence have as much to do with the way we choose to measure as they do with what the models are doing.”

We’re only now seeing and studying this behavior because of how large these models have become. Large language models train by analyzing enormous data sets of text —words from online sources including books, web searches, and Wikipedia—and finding links between words that often appear together. The size is measured in terms of parameters, roughly analogous to all the ways that words can be connected. The more parameters, the more connections an LLM can find. GPT-2 had 1.5 billion parameters, while GPT-3.5, the LLM that powers ChatGPT, uses 350 billion. GPT-4, which debuted in March 2023 and now underlies Microsoft Copilot , reportedly uses 1.75 trillion.

That rapid growth has brought an astonishing surge in performance and efficacy, and no one is disputing that large enough LLMs can complete tasks that smaller models can’t, including ones for which they weren’t trained. The trio at Stanford who cast emergence as a “mirage” recognize that LLMs become more effective as they scale up; in fact, the added complexity of larger models should make it possible to get better at more difficult and diverse problems. But they argue that whether this improvement looks smooth and predictable or jagged and sharp results from the choice of metric—or even a paucity of test examples—rather than the model’s inner workings.

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Line Chart

Three-digit addition offers an example. In the 2022 BIG-bench study, researchers reported that with fewer parameters, both GPT-3 and another LLM named LAMDA failed to accurately complete addition problems. However, when GPT-3 trained using 13 billion parameters, its ability changed as if with the flip of a switch. Suddenly, it could add—and LAMDA could, too, at 68 billion parameters. This suggests that the ability to add emerges at a certain threshold.

But the Stanford researchers point out that the LLMs were judged only on accuracy: Either they could do it perfectly, or they couldn’t. So even if an LLM predicted most of the digits correctly, it failed. That didn’t seem right. If you’re calculating 100 plus 278, then 376 seems like a much more accurate answer than, say, −9.34.

So instead, Koyejo and his collaborators tested the same task using a metric that awards partial credit. “We can ask: How well does it predict the first digit? Then the second? Then the third?” he said.

Koyejo credits the idea for the new work to his graduate student Rylan Schaeffer, who he said noticed that an LLM’s performance seems to change with how its ability is measured. Together with Brando Miranda, another Stanford graduate student, they chose new metrics showing that as parameters increased, the LLMs predicted an increasingly correct sequence of digits in addition problems. This suggests that the ability to add isn’t emergent—meaning that it undergoes a sudden, unpredictable jump—but gradual and predictable. They find that with a different measuring stick, emergence vanishes.

Portraits Brando Miranda  Sanmi Koyejo

Brando Miranda (left), Sanmi Koyejo, and Rylan Schaeffer (not pictured) have suggested that the “emergent” abilities of large language models are both predictable and gradual.

But other scientists point out that the work doesn’t fully dispel the notion of emergence. For example, the trio’s paper doesn’t explain how to predict when metrics, or which ones, will show abrupt improvement in an LLM, said Tianshi Li , a computer scientist at Northeastern University. “So in that sense, these abilities are still unpredictable,” she said. Others, such as Jason Wei, a computer scientist now at OpenAI who has compiled a list of emergent abilities and was an author on the BIG-bench paper, have argued that the earlier reports of emergence were sound because for abilities like arithmetic, the right answer really is all that matters.

“There’s definitely an interesting conversation to be had here,” said Alex Tamkin , a research scientist at the AI startup Anthropic. The new paper deftly breaks down multistep tasks to recognize the contributions of individual components, he said. “But this is not the full story. We can’t say that all of these jumps are a mirage. I still think the literature shows that even when you have one-step predictions or use continuous metrics, you still have discontinuities, and as you increase the size of your model, you can still see it getting better in a jump-like fashion.”

And even if emergence in today’s LLMs can be explained away by different measuring tools, it’s likely that won’t be the case for tomorrow’s larger, more complicated LLMs. “When we grow LLMs to the next level, inevitably they will borrow knowledge from other tasks and other models,” said Xia “Ben” Hu , a computer scientist at Rice University.

This evolving consideration of emergence isn’t just an abstract question for researchers to consider. For Tamkin, it speaks directly to ongoing efforts to predict how LLMs will behave. “These technologies are so broad and so applicable,” he said. “I would hope that the community uses this as a jumping-off point as a continued emphasis on how important it is to build a science of prediction for these things. How do we not get surprised by the next generation of models?”

Original story reprinted with permission from Quanta Magazine , an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

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