health data science phd programs

Health Sciences Informatics, PhD

School of medicine.

The Ph.D. in Health Sciences Informatics offers the opportunity to participate in ground-breaking research projects in clinical informatics and data science at one of the world’s finest biomedical research institutions. In keeping with the traditions of the Johns Hopkins University and the Johns Hopkins Hospital, the Ph.D. program seeks excellence and commitment in its students to further the prevention and management of disease through the continued exploration and development of health informatics, health IT, and data science. Resources include a highly collaborative clinical faculty committed to research at the patient, provider, and system levels. The admissions process will be highly selective and finely calibrated to complement the expertise of faculty mentors.    

Areas of research:

• Clinical Decision Support
• Global Health Informatics
• Health Information Exchange (HIE)
• Human Computer Interaction
• Multi-Center Real World Data
• Patient Quality & Safety
• Population Health Analytics
• Precision Medicine Analytics
• Standard Terminologies
• Telemedicine
• Translational Bioinformatics

Individuals wishing to prepare themselves for careers as independent researchers in health sciences informatics, with applications experience in informatics across the entire health/healthcare life cycle, should apply for admission to the doctoral program.

Admission Criteria

Applicants with the following types of degrees and qualifications will be considered:

• BA or BS, with relevant technical and quantitative competencies and a record of scientific accomplishment as an undergraduate; 
• BA or BS, with relevant technical and quantitative competencies and a minimum of five years professional experience in a relevant field (e.g., biomedical research, data science, public health, etc.); or
• MA, MS, MPH, MLIS, MD, PhD, or other terminal degree, with relevant technical and quantitative competencies

Relevant fields include: medicine, dentistry, veterinary science, nursing, ancillary clinical sciences, public health, librarianship, biomedical science, bioengineering and pharmaceutical sciences, and computer and information science. An undergraduate minor or major in information or computer science is highly desirable.

The application is made available online through Johns Hopkins School of Medicine's website . Please note that paper applications are no longer accepted. The supporting documents listed below must be received by the SOM admissions office by December 15 of the following year. Applications will not be reviewed until they are complete and we have all supporting letters and documentation.

• Curriculum Vitae (including list of peer-reviewed publications and scientific presentations)
• Three Letters of Recommendation
• Statement of Purpose
• Official Transcripts from undergraduate and any graduate studies
• Certification of terminal degree
• You are also encouraged to submit a portfolio of published research, writing samples, and/or samples of website or system development

Please track submission of supporting documentation through the SLATE admissions portal.

If you have questions about your qualifications for this program, please contact [email protected]

Program Requirements

The PhD curriculum will be highly customized based on the student's background and needs. Specific courses and milestones will be developed in partnership with the student's advisor and the PhD Program Director.

The proposed curriculum is founded on four high-level principles:

• Achieving a balance between theory and research, and between breadth and depth of knowledge
• Creating a curriculum around student needs, background, and goals
• Teaching and research excellence
• Modeling professional behavior locally and nationally.

Individualized curriculum plans will be developed to build proficiencies in the following areas:

• Foundations of biomedical informatics: e.g., lifecycle of information systems, decision support
• Information and computer science: e.g., software engineering, programming languages, design and analysis of algorithms, data structures.
• Research methodology: research design, epidemiology, and systems evaluation; mathematics for computer science (discrete mathematics, probability theory), mathematical statistics, applied statistics, mathematics for statistics (linear algebra, sampling theory, statistical inference theory, probability); ethnographic methods.
• Implementation sciences: methods from the social sciences (e.g., organizational behavior and management, evaluation, ethics, health policy, communication, cognitive learning sciences, psychology, and sociological knowledge and methods), health economics, evidence-based practice, safety, quality.
• Specific informatics domains: clinical informatics, public health informatics, analytics
• Practical experience: experience in informatics research, experience with health information technology.

Basic Requirements & Credit Distribution

• 15 "core" quarter credits (5 courses)
• 8 quarter credits of Student Seminar & Grand Rounds
• 60 elective quarter credits
• 6 quarter credits practicum/research rotation
• 36 mentored research quarter credits (12 in year 1, 24 in year 2)
• Research Ethics

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Health Data Science Concentration

Course information.

In addition to the existing core and elective courses in the Master of Science or PhD programs, the Health Data Science concentration features four core courses and five elective courses. Some of these courses are part of the current Master of Science program courses and some are new courses designed specifically for the Health Data Science concentration. One of the four core courses replace required courses for the traditional MS degree (BIOS 653: Applied Statistics III – Longitudinal Data Analysis).

Core and Elective Courses

Featured core courses in the Health Data Science concentration

Additional core courses can be found here.

Featured elective courses in the Health Data Science concentration

Course Selection Roadmap

Students' computing skills will be assessed for election of courses from the Health Data Science concentration and other degree core/elective courses. First-year MS students in Biostatistics can access information and advice from the department and faculty to plan their sequence of course selections.  Ongoing PhD students are able to complete this concentration. If they choose this route, some additional coursework is needed in order to meet the requirements of both the PhD and the HDS concentration.

HDS students must complete for their capstone courses (i) all four credits of BIOSTAT 699 and (ii) BIOSTAT 629 (1-2 credits). Biostat 629 will correspond to one or two comprehensive projects on mobile health, electronic health records, imaging data, omics data, etc.

Tables I and II below present two examples of course selections for a student with modest computing skills (e.g. having little knowledge of R programming) and for a student with strong computing skills (e.g. having extensive knowledge and experience in R, C++ and Python programming), respectively.

BIOS 607 is designed to prepare students with computing skills. In this way the Health Data Science concentration is more flexible and inclusive as a professional training program for workforce in health data analytics.

Table I. A possible sequence of course selections by an incoming MS student with modest computing skills, who begins with the three modules of BIOS 607.

Table II. A possible sequence of course selections by a first-year MS student with strong computing skills, who does not take BIOSTAT 607 but begins with BIOSTAT 625.

Note that there is one course (BIOS 653) not included in the curriculum of the Health Data Science concentration that is required by the PhD qualifying exams. Students interested in pursuing a PhD should take 653 in place of an elective the 2nd fall semester. Students already in the PhD program should take BIOS 653 for their qualifying exams.

Admissions Information

Students must be admitted to the Master of Science or PhD program in the University of Michigan School of Public Health's Department of Biostatistics. Once admitted, students will declare their intention to pursue the Health Data Science concentration at the end of their first year, by the end of May.

Have Questions?

For more information about the Health Data Science concentration, contact one of our graduate program coordinators.

Fatma Nedjari

Phone: 734-615-9812 Email: [email protected]

Nicole Fenech

Phone: 734-615-9817 Email: [email protected]  

Frequently Asked Questions

How/when do i apply for this program.

The Health Data Science concentration is not an option in the MS application, and thus there is no application procedure. Interested students should simply declare their intention to complete the Health Data Science concentration by May before their first (Fall) semester at Michigan Public Health by notifying a graduate program coordinator (Fatma Nedjari or Nicole Fenech). Students are encouraged to consult with their academic adviser about Health Data Science course selection.

Will I get in? Is there a cap? Am I automatically in? Are there more prerequisites?

There is no screening or selection procedure. This concentration program is open to all incoming Biostatistics MS students and operated as an automatic enrollment option. Interested students are encouraged to make a decision as soon as they arrive in their first Fall semester since the concentration courses are spread out over two years. As a specific track within the MS program, all Health Data Science courses require the same prerequisites as those in the core courses in the MS program.

When will I know if I get in the concentration program?

You may either notify a graduate program coordinator about your desire to pursue the Health Data Science subplan immediately after you decide to accept your admission offer to the Biostatistics MS program or in the beginning of your first Fall semester. At the stage of enrollment, simply follow the courses required by the Health Data Science concentration.

I have been admitted directly from a bachelor's degree program to the PhD program (or I definitely want to do the PhD program). Am I eligible for this Health Data Science concentration?

Yes, although masters' students interested in applying for the PhD program must be sure to include BIOS 653 (Theory and Application of Longitudinal Data Analysis) in their coursework.

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Public Health Data Science

The MS in Biostatistics Public Health Data Science Track (MS/PHDS) is designed for students interested in careers as biostatisticians applying statistical methods in health-related research settings. The MS/PHDS Track provides core training in biostatistical theory, methods, and applications, but adds a distinct emphasis on modern approaches to statistical learning, reproducible and transparent code, and data management. It is an appropriate program for students who intend to conclude their studies with the MS degree as well as those who want to pursue a PhD in biostatistics

All MS/PHDS candidates begin their studies in the fall semester. The length of the MS/PHDS program varies with the background, training, and experience of the candidate, but the usual period needed to complete the 36 credit MS/PHDS degree is two years (four semesters). In addition to fulfilling their course work, all MS/PHDS students also complete a one-term practicum and capstone experience.

Competencies

Through a curriculum of 36 credit hours of course work, a practicum, and the capstone experience, the MS/PHDS track provides students with the skills necessary for a career as a public health data scientist and a rigorous grounding in traditional biostatistics.

In addition to achieving the MS in Biostatistics core competencies, students in the PHDS Track gain the following specific competencies in the areas of public health and collaborative research, the foundations of applied data science, teaching biostatistics and biostatistical research. Upon satisfactory completion of the MS/PHDS, graduates will be able to:

Public Health and Collaborative Research

• Formulate and prepare a written statistical plan for analysis of public health research data that clearly reflects the research hypotheses of the proposal in a manner that resonates with both co-investigators and peer reviewers;
• Prepare written summaries of quantitative analyses for journal publication, presentations at scientific meetings, grant applications, and review by regulatory agencies;

Foundations of Applied Data Science

• Develop expertise in one or more statistical software and database management packages (often R and SQL, among others) routinely used by data science professionals;
• Implement a reproducible workflow for data analysis projects, including robust project organization, transparent data management, and reproducible analysis results;
• Develop and execute analysis strategies that use traditional statistical tools or modern approaches to statistical learning, depending on the nature of the scientific questions of interest;
• Identify the uses to which data management can be put in practical statistical analysis, including the establishment of standards for documentation, archiving, auditing, and confidentiality; guidelines for accessibility; security; structural issues; and data cleaning;

Teaching Biostatistics

• Review and illustrate selected principles of study design, probability theory, estimation, hypothesis testing, statistical learning, and data analytic techniques to public health students enrolled in introductory level graduate public health courses; and

Biostatistical Research

• Apply probabilistic, statistical, and data scientific reasoning to structure thinking and solve a wide range of problems in public health.

Course Requirements

MS/PHDS graduates are expected to master the mathematical and biostatistical concepts and techniques presented in the curriculum’s required courses. Each student's program is designed on an individual basis in consultation with a faculty advisor taking into consideration the student's prior educational experience.

Students who have mastered an academic area through previous training may have the corresponding course requirement waived. Some students, such as those with undergraduate majors in statistics or mathematics, may apply to have several courses waived. Students wishing to waive one or more courses must request approval in writing from their advisors and the Director of Academic Programs. These students must still complete a minimum of 36 points to earn the MS/PHDS degree.

Required Courses

Below is the required course work. Students consult their faculty advisors before registering for classes to plan their programs based on their individual background, goals, and the appropriate sequencing of courses. Waiver of any required courses (with prior written approval of their faculty advisor and the Director of Academic Programs) enables students to take other, higher level classes.

*Students who have strong math background and/or have taken basic machine learning methods, can substitute the P8106 Data Science II with P9120 Topics in Statistical Learning and Data Mining I. 

Students choose four or more courses from the list below or from alternatives approved by their academic advisors.

Sample Timeline

Below is a sample timeline for MS/PHDS candidates. Note that course schedules change from year to year, so that class days/times in future years will differ from the sample schedule below; you must check the current course schedule for each year on the course directory page .

Practicum Requirement

One term of practical experience is required of all students, providing educational opportunities that are different from and supplementary to the more academic aspects of the program. The practicum may be fulfilled during the school year or over the summer. Arrangements are made on an individual basis in consultation with faculty advisors who must approve both the proposed practicum project prior to its initiation, and the report submitted at the conclusion of the practicum experience. Students will be required to make a poster presentation at the department’s Annual Practicum Poster Symposium which is held in early May.

Capstone Experience

A formal, culminating experience for the MS degree is required for graduation. The capstone consulting seminar is designed to enable students to demonstrate their ability to integrate their academic studies with the role of biostatistical consultant/collaborator, which will comprise the major portion of their future professional practice.  

As part of the seminar, students are required to attend several sessions of the Biostatistics Consulting Service (BCS). The Consultation Service offers advice on data analysis and appropriate methods of data presentation for publications, and provides design recommendations for public health and clinical research, including preparation of grant proposals. Biostatistics faculty and research staff members conduct all consultation sessions with students observing, modeling, and participating in the consultations.

In the capstone seminar, students present their experience and the statistical issues that emerged in their consultations, developing statistical report writing and presentation skills essential to their professional practice in biomedical and public health research projects.

Paul McCullough Director of Academic Programs Department of Biostatistics Columbia University [email protected]

• Biostatistics and Data Science

The  Biostatistics and Data Science  program provides top-class training in biostatistics, as well as the analytic techniques used in data science to prepare students for the data-driven challenges of today's world. By providing a firm foundation on the theory of biostatistics and a hands-on experience in data analysis, the track prepares students for data analytic careers in the pharmaceutical industry, healthcare, biomedical sciences, academics, and general data analytics.

Each student acquires hands-on experience through a faculty-mentored research project that begins in the first term and culminates in a capstone/portfolio final project.

The Biostatistics and Data Science program has close ties to other programs within the Weill Cornell Medical College and Cornell University, the Department of Statistical Sciences at Cornell University, the Cornell Tech campus in New York City, and New York-Presbyterian Hospital. Full-time students can complete the M.S. in Population Health Sciences program with the Biostatistics and Data Science track in 12 months, and part-time students in 20 months. Students must complete at least 34 credits to graduate.

Unique Program

Our program in Biostatistics and Data Science is unique in its training in cutting edge data mining and machine learning techniques yet retains the rigor of a traditional Biostatistics program.

We keep our class size and student-to-faculty ratio low so that our students get the most personalized experience possible. Because of this, close mentorship with a faculty member throughout the entirety of the program is provided to all of our students. Many even continue their relationship well beyond becoming alumni and working in their careers.

Opportunities

Graduates, skilled in the management, analysis and visualization of big data, are prepared for challenging careers in the public and private biomedical, healthcare, insurance and pharmaceutical sectors, both in academia and the industry.

Students from all over the world join this program with backgrounds in science (e.g. statistics, mathematics, biology etc.), engineering, health and medicine. Their diversity creates a unique, collaborative learning environment.

Collaboration

Being in New York City is a huge asset for our program. Local institutions collaborating with Weill Cornell Medicine include NewYork-Presbyterian Hospital, Memorial Sloan Kettering Cancer Center, the Hospital for Special Surgery, The Rockefeller University, the State Department of Health, the New York City Department of Health and Mental Hygiene, and more. In addition, the tri-state area is home to one of the largest pharmaceutical hubs in the country, including Johnson and Johnson, Sanofi, Merck, Roche, Novartis, Bayer, Bristol-Myers Squibb, and Pfizer.

The culminating capstone experience allows students to gain valuable, real-world exposure under the guidance of experienced Biostatisticians and Data Scientists.

Our faculty are nationally recognized experts in biostatistics, health informatics, health policy, economics, health services research, cost-effectiveness, and comparative-effectiveness. Our NYC location allows for collaboration between experts and researchers at neighboring institutions, such as NewYork-Presbyterian Hospital, Hospital for Special Surgery, and Memorial Sloan Kettering Cancer Center.

Area of Study

This program provides comprehensive training in statistics concepts and programming which are taught hands-on with real-world applications used to solve the data-driven challenges of today’s world. Students augment this core training with the knowledge of healthcare through elective courses and gain invaluable real-world exposure during their capstone experience.

Student Handbook

To view the student handbook, click here .

Master's Tracks

• Health Informatics
• Health Policy and Economics

Apply to Weill Cornell Medicine Graduate School

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Faculty of Interest

Professor of Biomedical Informatics & Data Science; Vice Chair for Education, Biomedical Informatics & Data Science; Professor, Biostatistics

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Associate Professor of Biostatistics, Associate Professor of Ecology and Evolutionary Biology, Associate Professor of Management, and Associate Professor of Statistics and Data Science; Co-director, Public Health Modeling Concentration

Department Chair and Professor of Biostatistics; Affiliated Faculty, Yale Institute for Global Health; Director, Biostatistics and Bioinformatics Shared Resource

Assistant Professor of Biostatistics (Health Informatics)

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Assistant Professor of Biostatistics; Co-Training Director, Health Informatics MS

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Elihu Professor of Biostatistics and Professor of Ecology and Evolutionary Biology; Co-Leader, Genomics, Genetics, & Epigenetics Research Program

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Associate Professor of Biostatistics; Associate Professor, Biomedical Informatics & Data Science

Ira V. Hiscock Professor of Biostatistics, Professor of Genetics and Professor of Statistics and Data Science; Affiliated Faculty, Yale Institute for Global Health

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UCLA Graduate Programs

Graduate Program: Data Science in Health

UCLA's Graduate Program in Data Science in Health offers the following degree(s):

Master of Data Science in Health (M.D.S.H.)

With questions not answered here or on the program’s site (above), please contact the program directly.

Data Science in Health Graduate Program at UCLA Suite 51-254 CHS Box 177220 Los Angeles, CA 90095-1772

Visit the Biostatistics Department’s faculty roster

COURSE DESCRIPTIONS

Visit the registrar's site for the Biostatistics Department’s course descriptions

• Admission Requirements
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(310) 825-5250

[email protected]

MAJOR CODE: DATA SCIENCE IN HEALTH

DiscoverDataScience.org

Ph.D. in Health Informatics – Guide to Choosing a Great Program

By Kat Campise, Data Scientist, Ph.D.

Undoubtedly, everyone in the U.S. will access the health care system at some point in their lives. Moreover, we’re in an era where the large population of Baby Boomers and elder Gen X’ers are increasing their health care utilization. This translates into a greater need for massive data and information collection, storage, and dissemination on the part of health care providers, agencies, and organizations.

A Ph.D. in Health Informatics is designed for students looking for a career in research or academia.

For those hoping to a pursue a career in industry, a master’s in health informatics is probably a better fit.

Furthermore, the Federal government has established regulatory controls over data privacy and limits who can access medical records (i.e., HIPAA ), and there may be additional state laws that require adherence as well. As a consequence, those who handle or manage medical data need to have specific knowledge, skills, and abilities in HIPPA compliant database and information systems.

On an additional note, HealthTech and InsurTech are industries that will experience substantial growth as electronic medical records become the norm. The continued uptick in medical and general health wearables, which will transmit real-time or batched data, will also push more data into health care databases.

For these reasons, the need for health informatics professionals is growing at a pace that is faster than average when compared to other professions. Although the demand for health informatics isn’t as widely advertised as data science or software engineering , the career opportunity does exist for those who are interested in helping to improve the health care system from a technological and informational perspective.

Health Informaticians: What Do They Do, Exactly?

While each employer may have a different title within the framework of health informatics, there are essentially two primary roles: health information technician (HIT) and the health information manager (HIM). Both positions have important responsibilities that help health care providers and the overall health care system to deliver high-quality health care.

Health Information Technicians

Per the Bureau of Labor and Statistics Occupational Outlook Handbook, health care technicians “ organize and manage health information data .” Health information technology professionals may assist in building the information system, documenting patient data, determine the best method for managing information transmitted by each health care stakeholder (e.g., doctors, nurses, pharmacists, patients, etc.), and ensure the accuracy of patient/provider data as it funnels through the information system. Typically, health information technician is an entry-level position that frequently requires at least an associate’s degree or certification in health information technology.

Health Information Managers

Health information managers oversee the HITs (specifically) and the health information management department (in general). Moreso than health technicians, health information managers are likely to assist with the design and implementation of health information systems. They have the added responsibility of managing budgets which means that candidates for this position will need to have the knowledge and practical experience within the business side of health care. Familiarity or expertise with the existing database and information systems utilized within the health care field is also an employer expectation. Many employers require either a Registered Health Information Administrator (RHIA) or a Registered Health Information Technician (HRIT) certification along with a Bachelor’s Degree in Health Information Technology and 5 years experience in an HIM capacity. A Ph.D. in Health Informatics may override the certification requirements and place employee candidates at the top of the application pile. One pro tip is that, if you’re determined to enter the health informatics career path, networking with those already in the field tends to yield higher responses during your job search. The upside of a Ph.D. is that most programs require submitting academic papers and presenting research at industry conferences. This is a prime opportunity to make connections with potential employers.

4 Steps to Choosing an On-Campus Ph.D. in Health Informatics

Ph.D. programs are arduous, and a Ph.D. in Health Informatics is no exception. Everyone who is considering the completion of a Ph.D. needs to understand that reality before they commit the next 4 to 7 years saturating themselves with research and writing. There are many hoops to jump through at each stage of the Ph.D. journey. Since Ph.D. level education is geared towards churning out academics, meaning that graduates stay in academia as a career, many Ph.D. graduates have a challenging time trying to transition from academia to their target industry. You’ll still need to market yourself to employers just like everyone else. Having a Ph.D. doesn’t magically bring employers to your door, but it can signal that you’ve attained in-depth expertise in the field. It will largely be up to you to clearly communicate the value you can provide to the organization, and how having a Ph.D. helps support that value.

Step 1: Determine your location and time availability

Even in the age of online degrees, Ph.D. programs continue to be primarily campus-based. Added to this is the fact that not all universities carry the same Ph.D. programs, which holds true for a Ph.D. in Health Informatics. Therefore, you’ll need to do some research to determine whether or not any of the local universities offer this degree program. If not, and you’re specifically focused on health informatics, then it’s highly likely that you’ll be faced with the possibility of moving to another location to complete the degree. Likewise, most Ph.D.s are full-time undertakings. Not only should you factor in the total time from start to completion (e.g., 4 to 7 years), but also whether or not you can manage both the Ph.D. requirements and a job. Funneling down a bit further, daily or weekly travel time between home, school, and work (if you do need to also maintain a job), tend to cut into study time. Granted, if reliable public transportation is available, then you can definitely utilize the time for additional study.

Step 2: Review the curriculum

Is health informatics of deep interest to you? You’ll be performing a profound analytical dive into the subject over an extended period, and there may be several different program tracks to choose from. For example, the University of Minnesota’s on-campus Ph.D. in Health Informatics offers four different concentration options: Clinical Informatics, Data Science and Informatics for Learning Health Systems, Translational Bioinformatics, and Precision and Personalized Medicine Informatics. Reviewing the curriculum of each along with comparing and contrasting the course completion requirements will help for identifying any knowledge gaps that may be the cause for additional “catching up” either through self-study or taking additional courses. Returning to Minnesota’s Ph.D. tracks, both the Bioinformatics and Data Science sub-disciplines have machine learning coursework. If you’ve not yet been exposed to machine learning in any capacity, even though you’re interested in developing that skill, then you’ll need to spend more time and money to achieve a certain proficiency level. Accordingly, your interest level and the available curriculum are substantial factors in successfully attaining a Ph.D.

Step 3: Perform a cost-benefit analysis

There is a cost trade-off to examine when assessing a decision to invest copious amounts of time and money into continuing formal education. As discussed above, you’ll be focussing a massive amount of energy into navigating the Ph.D. demands: attending courses, performing qualitative and quantitative research, writing extensive academic papers, attending conferences, and preparing a dissertation (which frequently involves assembling a committee). If you’re also employed during this time, especially full-time, it’s very easy to become drained by a lack of work-school-life balance. Also, you’ll be applying your knowledge within an academic context, which may not directly apply to the work performed at your job. Or, if you’re able to focus on the Ph.D. in Health Informatics on a full-time basis, there is a high probability that you’ll lose earnings potential while you’re finishing the degree. Then, there are the actual costs of the Ph.D. program itself. If you’re entering a university where you’re an established resident of the state (this is true mainly for state schools), then tuition will be lower. However, tuition and fees even for state residents can range from just below $16,000 to over $35,000 , including tuition, fees, books, and living expenses.

Step 4: Analyze the admission requirements

Overwhelmingly, one of the main admission requirements for a Ph.D. in Health Informatics (and just about any other Ph.D. program) will be attaining a minimum score on the GRE. From there, the necessary undergraduate or master’s degree and GPA average will tend to diverge depending on the university. For instance, if the Ph.D. in Data Science and Informatics for Learning Health Systems from the University of Minnesota is your goal, then you’ll need at least a 3.5 GPA, a minimum of two courses in a life or health science (6 semester credits), and the completion of the following college math courses: calculus, linear algebra, statistics . All of the above is only half of the admission requirements for most Ph.D. programs. You’ll also likely be tasked with completing a personal statement that describes your research interests, letters of recommendation from supervisors who have direct knowledge of prior academic work (usually 2 to 3 in number), and an interview; sometimes, the interview can be conducted via web conferencing, but many universities require an in-person interview. All of this equates to more time and money invested even before you are admitted.

School Listings

University of Arkansas at Little Rock – Little Rock, Arkansas Ph.D. in Bioinformatics

Delivery Method: Campus GRE Required: Required 2020-2021 Tuition: $320 per credit (resident), $725 per credit (non resident)

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PhD in Data Sciences for Global Health

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How to apply.

The PhD program in Data Sciences for Global Health, jointly offered by BITS Pilani and the One Health Trust (OHT), offers training in global health issues and cutting-edge research methodology with rigorous fieldwork and data analysis. This program provides full-time, advanced education in global health plus expertise in qualitative and statistical/quantitative skills leading to an interdisciplinary degree. The BITS Pilani and OHT faculty have vast research experience in infectious disease dynamics, antimicrobial resistance, vaccines and immunization, environmental health, gender equity and livelihoods, health and development, health systems, and economics.

Students will spend part of their tenure in the program at the BITS Pilani campus and the other period housed at the Nimai Valley Center.

Applicant Brochure (2022–2023)

If you have any questions, please contact [email protected] .

Registration for the next cohort starting in January 2025 will open in August 2024!

Program Curriculum and Requirements

The students must complete six core courses covering three main subjects (24 credits) during the first year. Before the end of their second year, students will defend their thesis proposal and research plan. From their third year onwards, PhD candidates will present their work at seminars, conduct fieldwork, and communicate their research outcomes through research papers that will together form a PhD dissertation. Students must maintain a minimum grade of D and CGPA of 5.50 in all semesters. Each academic year will have two semesters.

First Year (first and second semester)

The first year will involve coursework in the following six core courses:

• Global Health I and II
• Data Sciences (including Research Methodologies) I and II
• Health Economics and Policy I and II

The coursework will help students build a strong theoretical foundation in global health and equip them with data skills. The first-year activities will take place on the BITS Pilani campus. A qualifying exam will be held at the end of the first year. Students will be promoted to the second year only if they pass at least two of their main subjects. The exam will include a written test and viva on the courses taught. BITS and OHT will jointly conduct the written exam and viva.

Second Year (third and fourth semester)

In the second year, students will draft a detailed research proposal to undertake thesis work and submit to their advisory committee for review. The students should take independent study/classes from faculty members from BITS-Pilani or OHT, in their research areas of interest (directed individual study), as they work on their research proposal and papers. A rotation method can be used to learn from various faculty members. Students are also encouraged to learn grant writing from their notional supervisor(s) and apply for research grants. At the end of each semester, students are expected to submit term papers, based on their research.

Students are strongly encouraged to find a potential advisor(s) during their second year. The main advisor will be from BITS Pilani and their co-advisor can be from OHT. Students will also choose a doctoral advisory committee (DAC) consisting of two members, from among the faculty members of BITS Pilani and OHT.

A candidacy/oral exam will be held at the end of the fourth semester. The exam will include an oral presentation on the research proposal developed in the second year. The proposal will be defended in the presence of a peer group and faculty of the concerned departments. Following the approval of the research proposal, students can then register for thesis units (maximum of 10 units per semester). A minimum of 40 thesis units should be completed to submit the thesis for examination.

Third Year through finishing the PhD program (fifth semester and beyond)

After advancing to Ph.D. candidacy, students are expected to present their progress at least twice each semester to their supervisors and DAC. Additionally, they are expected to submit progress reports to their respective DAC members at least once per semester. Students are also encouraged to present their research in seminars or conferences organized by BITS, OHT, and elsewhere.

• Field Work: Students are required to undertake field visits at OHT’s Nimai Valley Center. They may conduct quantitative or qualitative data collection corresponding to their research interests.
• Dissertation Defense: The student will prepare their thesis in consultation with their team of supervisors and present/defend to their DAC. They will be required to write three research papers, which will form their dissertation, and publish in peer-reviewed journals to graduate.

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• Ramanan Laxminarayan
• Thomas P. Van Boeckel
• Deepshikha Batheja
• Geetanjali Kapoor
• Erta Kalanxhi
• Arindam Nandi
• Samantha Serrano

• Is there a fee to apply for this program?

The application fee is around INR 2,600. This is subject to revisions, and you can verify fees at https://www.bitsadmission.com/phdmain.aspx

• What is the application deadline?

The application deadline is typically in May-June with the semester starting in late July or early August. Intake for this program is yearly.

• Am I eligible to apply for this program?

We welcome applications from all professional, geographic, cultural, and socioeconomic backgrounds, with no age restriction. Meeting the minimum eligibility criteria does not guarantee admission into the program. For more information, please refer to the BITS PhD admissions prospectus.

Minimum eligibility criteria:

• ME/MTech/MPharm/MBA/MPhil/MSc/BE/BPharm or an equivalent degree: minimum of 60 percent aggregate
• MA: minimum of 55 percent aggregate
• MBBS/BDS/BVSc/MD/MDS/MVSc/BAMS/BHMS/BUMS/allied: minimum of 55 percent aggregate.
• My previous degree is from outside of India. What documents will I need to submit for registration if I am accepted?

International students will be required to provide an appropriate grade conversion to the Indian grading system, which has to meet the eligibility listed above. This will be in addition to the document checklist for the application package detailed in the BITS PhD admissions prospectus.

• Does the application process include an interview?

Shortlisted applicants will be interviewed about their knowledge of global health, data sciences, and research interests. OHT will participate in the interviewing panel. Given the diverse backgrounds of applicants, applicants are expected to be proficient in their previous degree(s) and have an aptitude for the other domains in the program. No written exam will be offered, but grades from previous degrees (transcripts), statements of purpose (SOPs), and letters of recommendation (LORs) will be considered.

• What is the expected time within which I can expect to receive a decision on my application?

You can expect to receive a decision on your application within six to eight weeks of the close of the application window.

• What is the expected length of the program?

All admitted candidates will be required to do the standard coursework in the first two semesters. Students must complete six core courses covering three main subjects (24 credits) during the first year. Before the end of their second year, students will defend their thesis proposal and research plan. From their third year on, PhD candidates will present their work at seminars, conduct fieldwork, and communicate their research outcomes through research papers that will write a PhD dissertation. PhD candidates must submit a thesis within five years to successfully complete the degree. For more information, please refer to the BITS PhD admissions prospectus. Students may take a maximum of seven years to finish their PhD due to unforeseen circumstances, with appropriate approvals from their dissertation committee.

• Is this an on-campus full-time program or a hybrid program?

This PhD is offered only as an on-campus full-time program. Students may be able to take courses online, which are offered at the other BITS campuses, as part of their degree requirements.

• Is it possible to change your supervisor after being assigned one at the time of offer of acceptance?

You will need to file a formal request for a change of supervisor and pending approval from an internal committee at BITS, you can change your assigned supervisor.

• What are the locations of the BITS Pilani campuses that offer courses applicable to this program?

You can find the addresses for each campus below:

BITS Pilani, Hyderabad Campus

Jawaharnagar, Shamirpet Mandal Medchal-Malkajgiri District Hyderabad 500078 Telangana

Google Maps

BITS Pilani, Goa Campus

NH 17B, Bypass, Road Zuarinagar, Sancoale Goa 403726

BITS Pilani, Pilani Campus

Vidya Vihar Pilani Rajasthan 333031

• What is the fee structure for this program?

The following are the details of the fees in INR payable by all students admitted to the PhD Program in the academic year 2025-2026 at BITS- Pilani, Pilani Campus.

* Payable at the time of admission; # Payable at the time of thesis submission

Financial Assistance:

Full-time PhD students admitted into the PhD program are eligible to be considered for a fellowship of INR 34,000/- or INR 37,000/- per month as per intake qualifications. Consideration for a fellowship will be as per institute norms, details of which are available in the PhD brochure on the admission website. It will be obligatory on the part of every admitted full-time student to undertake eight hours (per week) of work as assigned to her/him by the institute.

• What are the potential sources of financial assistance given to PhD students?

All successfully admitted students will have financial support through one of the following sources:

• Self-funded fellowships such as UGC/CSIR NET JRF , DBT JRF/SRF , ICMR JRF/SRF , DST Inspire
• A BITS Pilani Fellowship, which will include working as a teaching assistant (TA). The stipend/scholarship is in lieu of the TA duties.
• What is the expected stipend?

All admitted students who do not have self-funded fellowships will receive a BITS Pilani Fellowship of INR 34,000/month during the first year, provided for up to five years from the date of admission. It can be enhanced to INR 37,000 per month from the second year on and to INR 40,000/42,000 per month in the third year, based on the student’s performance and output. The fellowship amount is usually aligned with the norms of the Government of India.

• If I have a self-funded fellowship such as JRF/SRF, will I still be expected to have teaching duties on the BITS campus?

Yes, you will still be required to carry out teaching assistant (TA) duties every semester you are enrolled in the program.

• As part of being a teaching assistant (TA), how many hours of classes am I expected to assist in a week?

On an average, approximately 8 hours a week.

• Does OHT provide research assistantships (RA) to complement the stipend?

Yes, OHT provides research opportunities to PhD students to earn additional income on top of their stipend.

• Does BITS or OHT provide on-campus accommodation?

Students will be expected to be at one of the BITS campuses in their first year. From the second year onwards, students are encouraged to spend time on one of the BITS campuses or OHT India campus, depending on their research area of interest. OHT will be able to provide housing on campus (expected completion: 2024/2025). Students are expected to cover their cost of stay/living at both institutions.

• Can PhD students live off-campus and attend classes?

Yes, PhD students can live off-campus and commute with their own vehicles or any other available public modes of transportation.

• Is there any accommodation for TAs assisting classes remotely?

There usually is no provision for such requests. However, temporary accommodations can be discussed on a case-by-case basis.

• Are there any qualifier exams to confirm one’s candidature as a PhD student? Are multiple attempts of the exam allowed?

Yes, apart from the semester exams for the courses a candidate is taking, candidates are expected to pass two qualifier exams to maintain their candidacy as a PhD student. Students are expected to choose a primary and a secondary research area for their thesis and to write qualifier exams in these areas. The areas can be from two different departments. The candidate should consult the DRC (Departmental Research Committee) to know about the areas offered and the exam modalities. Every student has until the end of the second year to appear for and clear their qualifier exams. A maximum of two attempts are allowed to clear qualifier exams and both the areas must be cleared together.

Eligible students may apply for the PhD program in Data Sciences for Global Health, from August 2023 – January 2025. Online application forms will be available from December 2023 to August 2024. The number of students admitted will vary based on the availability of positions in the department, funding, and the merit of applicants.

Applications to the PhD program are invited from candidates with a master’s degree in any basic science or liberal arts discipline. We also accept applications from candidates with a bachelor’s degree in medical, dental, veterinary, pharmaceutical, or alternative health sciences and engineering. Applicants from other fields are also encouraged to apply.

The minimum eligibility requirements for admission are as follows:

• ME / MTech / MPharm / MBA / MPhil: minimum of 60% aggregate
• MSc / BE / BPharm or an equivalent degree: minimum of 60% aggregate
• MA: minimum of 55% aggregate
• MBBS / BDS / BVSc / MD / MDS / MVSc / BAMS / BHMS / BUMS / allied

Applicants should submit the following:

Statement of research purpose (maximum two pages), indicating the candidate’s academic background, broad research interests, career goals, and how a PhD in Data Sciences for Global Health from BITS Pilani–OHT will advance their career goals.

Two letters of recommendation

The shortlisted applicants will be interviewed about their knowledge of global health, data sciences, and research interests. OHT will participate in the interviewing panel. There will be no written exam, but grades from previous written exams will be considered.

If you have any questions, please contact  [email protected] .

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Health Data Science

• Entry year 2024
• Duration Full time 3 - 4 years, Part time 4 - 7 years

The PhD in Health Data Science provides research training in developing applied informatic and analytic approaches to data within health-related subjects such as medicine and the biomedical, biotechnological, and bioengineering sciences.

You will join the programme with a supervisory panel composed of academics working in health data science more broadly. Throughout the programme, and particularly during your first year, you will be encouraged to engage in training opportunities at Lancaster and elsewhere to develop both your research skills and subject-specific knowledge and abilities. Throughout your studies, you will focus on novel scientific research, developing best practice in interpreting and communicating new scientific methods and findings.

Your department

• Lancaster Medical School Faculty of Health and Medicine
• Telephone +44 (0)1524 592032

Entry requirements

Academic requirements.

2:1 Hons degree (UK or equivalent) in a relevant subject.

We may also consider non-standard applicants, please contact us for information.

If you have studied outside of the UK, we would advise you to check our list of international qualifications before submitting your application.

Additional Requirements

As part of your application you will also need to provide a viable research proposal. Guidance for writing a research proposal can be found on our writing a research proposal webpage.

English Language Requirements

We may ask you to provide a recognised English language qualification, dependent upon your nationality and where you have studied previously.

We normally require an IELTS (Academic) Test with an overall score of at least 6.5, and a minimum of 5.5 in each element of the test. We also consider other English language qualifications .

If your score is below our requirements, you may be eligible for one of our pre-sessional English language programmes .

Contact: Admissions Team +44 (0) 1524 592032 or email [email protected]

Fees and funding

The tuition fee for students with home fee status is set in line with the standard fee stipend provided by the UK Research Councils. The fee stipend for 2024/25 has not been set. For reference, the fee stipend for 2023/24 was full-time £4,712.

The international fee for new entrants in 2024/25 is full-time £26,490.

Depending on the nature of the research project, an additional programme cost may be charged. This additional fee will contribute towards the costs incurred on specific research projects. These costs could include purchasing specialist consumables, equipment access charges, fieldwork expenses and payments for transcription/translation services.  Normally any additional charge will not exceed a maximum of £9,720 but this could be increased in exceptional circumstances.

Applicants will be notified of any specific additional programme cost when the offer of a place is made.

General fees and funding information

There may be extra costs related to your course for items such as books, stationery, printing, photocopying, binding and general subsistence on trips and visits. Following graduation, you may need to pay a subscription to a professional body for some chosen careers.

Specific additional costs for studying at Lancaster are listed below.

College fees

Lancaster is proud to be one of only a handful of UK universities to have a collegiate system. Every student belongs to a college, and all students pay a small College Membership Fee  which supports the running of college events and activities. Students on some distance-learning courses are not liable to pay a college fee.

For students starting in 2023 and 2024, the fee is £40 for undergraduates and research students and £15 for students on one-year courses. Fees for students starting in 2025 have not yet been set.

Computer equipment and internet access

To support your studies, you will also require access to a computer, along with reliable internet access. You will be able to access a range of software and services from a Windows, Mac, Chromebook or Linux device. For certain degree programmes, you may need a specific device, or we may provide you with a laptop and appropriate software - details of which will be available on relevant programme pages. A dedicated  IT support helpdesk  is available in the event of any problems.

The University provides limited financial support to assist students who do not have the required IT equipment or broadband support in place.

For most taught postgraduate applications there is a non-refundable application fee of £40. We cannot consider applications until this fee has been paid, as advised on our online secure payment system. There is no application fee for postgraduate research applications.

For some of our courses you will need to pay a deposit to accept your offer and secure your place. We will let you know in your offer letter if a deposit is required and you will be given a deadline date when this is due to be paid.

The fee that you pay will depend on whether you are considered to be a home or international student. Read more about how we assign your  fee status .

If you are studying on a programme of more than one year’s duration, the tuition fees for subsequent years of your programme are likely to increase each year. Read more about  fees in subsequent years .

Scholarships and bursaries

You may be eligible for the following funding opportunities, depending on your fee status and course. You will be automatically considered for our main scholarships and bursaries when you apply, so there's nothing extra that you need to do.

Unfortunately no scholarships and bursaries match your selection, but there are more listed on scholarships and bursaries page.

If you're considering postgraduate research you should look at our funded PhD opportunities .

We also have other, more specialised scholarships and bursaries - such as those for students from specific countries.

Browse Lancaster University's scholarships and bursaries .

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The information on this site relates primarily to 2024/2025 entry to the University and every effort has been taken to ensure the information is correct at the time of publication.

The University will use all reasonable effort to deliver the courses as described, but the University reserves the right to make changes to advertised courses. In exceptional circumstances that are beyond the University’s reasonable control (Force Majeure Events), we may need to amend the programmes and provision advertised. In this event, the University will take reasonable steps to minimise the disruption to your studies. If a course is withdrawn or if there are any fundamental changes to your course, we will give you reasonable notice and you will be entitled to request that you are considered for an alternative course or withdraw your application. You are advised to revisit our website for up-to-date course information before you submit your application.

More information on limits to the University’s liability can be found in our legal information .

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Structured PhD Program in Health Data Sciences

The PhD Program in Health Data Sciences at the Charité is hosted in English and aimed at qualified young scientists interested in:

• deepening their methodological knowledge in the fields of biostatistics, epidemiology, public health, meta-research, population health science and medical informatics.
• further expanding their competence in research and teaching.

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• PhD in Health Data Sciences

PhD Program in Health Data Sciences

Upon successful completion of the program, students will be awarded the academic degree of "Doctor of Philosophy" (PhD).

We are no longer accepting applications for entrance into our October 2024 cohort.

The deadline to submit applications for entrance into the October 2024 HDS PhD cohort was February 29, 2024 (23:59 CET).

The application window for our October 2025 HDS PhD Cohort will open in the beginning of 2025. Please check back in the autumn of 2024 for further details. 

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HDR UK-Turing Wellcome PhD Programme in Health Data Science

This truly outstanding and generously funded four-year programme at top UK universities provides you a pathway to join the UK’s leaders in health data research.

What this unique PhD programme offers you

Four-year programme: An initial foundation year allows students to gain real experience and insight into health data research.

Hosted by leading universities: Our host universities are among the very best in health data research.

Nurturing each student: Our programme aims to identify the particular abilities and interests of each student, and gear their PhD experience to effectively develop them.

Leadership Programme: Students benefit from a bespoke expert-led programme to develop the skills they need to understand, collaborate and influence others.

Generous funding: Students have their tuition fees (UK Home rate), college fees (where applicable), research expenses and travel costs paid and receive an enhanced, tax-free stipend with increases every year. (Y1 outside London: £23,955, Y1 in London: £25,954)

Building networks and experience: We actively support students in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience. This includes a post-PhD bursary to support your next career step.

Team spirit: Strong relationships are built between our entire cohort of students through joint activities that build a genuine team spirit.

Personal support:  Each student has their own Director of Studies who is an additional point of contact during their time with us. All students are also further supported by the PhD team.

“The PhD programme has enabled me to gain first-hand experience in modern health data science approaches. It’s a truly unrivalled opportunity.”  Steven Wambua

Who is the PhD programme for?

We recruit enthusiastic, talented students who want to use data-driven research to develop and shape the UK’s response to the most complex health challenges of our times.

Applicants must have (or be on track to obtain):

• A first class or 2:1 undergraduate degree in statistics, mathematics, computer / data science, physics or an allied subject  or
• Another undergraduate degree subject and outcome but can demonstrate their suitability for this programme through additional qualifications or research experience.

Active or currently registered health care professionals   are not eligible and should consider the Wellcome PhD Fellowships for Health Professionals .

Applicants also need to meet the following criteria:

• Successful admission to the specified degree programme at one of our partner universities. Students will be expected to meet the admissions requirements of that department and university but do not need to hold the offer at the point of application.
• Two satisfactory academic or relevant references.
• Proof of a legal right to study in the UK or ability to satisfy the current requirements of UK Visa and Immigration.

Training is in-person, hybrid and virtual throughout the first year.

We are committed to a diverse and inclusive research culture . We welcome those who are returning from the workplace, international candidates and everyone underrepresented in STEM and academia. For further details see our FAQs .

We cannot accept applicants who are looking for a part-time PhD or those who are aiming to study whilst continuing to be employed elsewhere.

We aim to accommodate specific needs and personal circumstances. Please make us aware of individual circumstances when applying or contact us directly at  [email protected] . Please note our  applicant privacy notice .

If you have questions or require adjustments to the application process, please contact us below via email or telephone (+44 (0)770 847 8846).

There are no nationality restrictions and international students are able to apply. However, applicants are advised the award only covers fees at the UK/Home level. International students will be required to secure an additional scholarship from Queen’s University Belfast (after receiving a offer from us at interview) to cover the difference between Home and Overseas fees. This will limit the university choices available:

(Please be aware that these are usually highly competitive and will need to be applied for separately in your application to Queen’s University Belfast post-offer. A successful application to the PhD programme does not guarantee a fee waiver or scholarship. We do not accept applications from candidates who are self-funding.)

We are currently only recruiting for Queen’s University Belfast.

These are only initial programmes of study for Year 1. Students may transfer to a new university programme from Year 2 after research projects have been confirmed.

Is this the PhD future for you?

Watch our Applicant Open Day hosted by our current students to find out more about the programme and whether it’s for you.

Applications are currently: Closed

The application process.

Details required:

• Contact details
• Details and transcripts of university qualification(s)
• Any relevant job history
• Answers to personal-statement type questions (250-words maximum for each answer)
• Contact details for two referees
• There is no need to apply to the university, submit a research proposal, provide IELTS scores or contact supervisors at this stage

Submitted applications will first be checked for eligibility and then will undergo a first stage review. This will involve triage by the PhD Team in April 2024 . Successful applicants will be invited to an interview in May 2024 .

After receiving an offer, applications will be invited to apply to Queen’s University Belfast.

Selection criteria

Applicants should demonstrate that they meet the following criteria:

* These criteria will be assessed at interview via a pre-interview exercise.

HDR UK reserves the right to reject applicants who do not meet the criteria at any stage. Regretfully, we can only provide feedback for candidates who reach interview.

Programme Structure

The four-year programme is divided in two. There is an initial Foundation Year followed by a three-year research project. The first year combines the best in university-based training with HDR UK-led national activities. And we support students to produce game-changing research plans and their projects are backed by substantial research funding.

Foundation year

3-5 day immersion events allow students to gain insight into the work of HDR UK, and our academic, clinical and industry partners. Courses may be residential (expenses provided) with up to a week away from their home university or online. Students undertake an intensive deep dive into an important area of health data science. Immersion topics include risk prediction, oncology, clinical trials, epidemiology and bioinformatics. Past immersion weeks have been hosted by the Universities of Birmingham, Manchester, Oxford and University College London and the European Bioinformatics Institute.

The immersion events encourage students to work together and stimulate new interactions:

• Axes of Prognosis
• The Different Facets of Data

Research areas

PhD research projects can be linked to The Institute’s:

• Research priorities
• Research hubs
• Partnerships

Team working

Students operate as a national cohort and work collaboratively with others, overcoming traditional institutional silos. Students are registered with a  partner university  but can draw on academic expertise from across the HDR UK network and are supported to formulate research activities that bring together experts from across the UK.

• You can contact us at [email protected]   or phone (+44 (0)770 847 8846). 
• For details of how we process applicants’ data see PhD Applicant Privacy Notice .

Students have access to graduate-level courses and research project rotation in their university to introduce them to different areas of health data science and enable them to develop a bespoke research project under the guidance of our expert university leads.

Regular workshops and short courses introduce students to the work of HDR UK experts across our hubs, themes and priority areas and to external organisations. Past contributors have included NHSX, IQVIA and AstraZeneca.

Immersion and workshop events allow students to better understand the wider health and social care landscape and accelerate their potential to become sector leaders. They also enable students to develop more ambitious PhD research projects by stimulating collaboration with external academics, industry-based organisations, or by using national data infrastructure.

Training is provided by academic, industry and NHS experts to promote personal and professional development in leadership capability, cross-sector collaborative skills and inter-disciplinary working. In particular, HDR UK is committed to working with public and patients to build increased trust in health data research as well as designing solutions focused on improving patient outcomes and experience. Students will develop communication and collaborative skills to help put them at the forefront of this mission.

At the end of the Foundation Year students design a bespoke three-year research project and a multi-disciplinary supervision team based on their training experiences.

Research proposals will be rigorously reviewed by expert academics and public-patient representatives to ensure they are of the highest standards in terms of ambition, scientific methodology and impact on patient outcomes.

The research will be carried out at their home university and could be linked to HDR UK  research priorities ,  research hubs  or  partnerships .

This includes short immersions plus  longer practical real-world projects with businesses and other organisations at the cutting edge of everything from medical devices, to life sciences, to vaccines. Students also learn about leadership theory and attend specially-convened seminars from senior figures in relevant areas of healthcare.

Networks and experience: Students will be actively supported in building networks and contacts in academia, the NHS and industry as well as taking internships and other opportunities to gain real-world experience.

Team working: Students operate as a national cohort, building strong relationships through joint activities and overcoming traditional institutional silos.

Workshops: Regular workshops and short courses introduce the work of HDR UK experts and to external organisations.

Immersion events: These allow students to better understand the wider health and social care landscape and accelerate students’ potential to become a sector leader. They also enable them to develop an ambitious PhD research project.

Researcher development: Training is provided by academic, industry and NHS experts to promote personal and professional development in cross-sector collaborative skills, communication and inter-disciplinary working.

“Our Leadership Programme will give PhD students the chance to develop the practical skills they need to bring people together to use health data science to deliver much-needed innovations and advances in health and care,”  Professor Peter Bannister

Our partners

Programme partners include NHS Digital, AstraZeneca, Moorfields Eye Hospital NHS Foundation Trust, and University Hospitals Birmingham.

More broadly it will work with winners of the NHSX AI Innovation Award , which funds and supports promising artificial intelligence technologies in health and care. There will also be opportunities with businesses on the DTI listed top 100 digital health innovators which are using big data for healthcare innovation.

Master’s Degree Scholarships

We offer 10 annual Master’s degree scholarships worth £10,000 for students with an interest in dementia or diabetes research.

Undergraduate Summer Internship in Health Data Research

Apply for a summer work placement in health data research at a UK research organisation, with an HDR UK-Wellcome Biomedical Vacation Scholarship

Join the HDR UK Alumni Network

HDR UK’s online Alumni Network brings together the amazing people who have been part of our training and education programmes.

Our host universities

- - - - Meet our PhD students

Our PhD students come from a wide range of backgrounds - discover who they are and what their experiences have been as part of the PhD programme

Meet the PhD Programme team

Our wider team consists of leading experts in disciplines including theoretical physics, computer science, mathematics and statistics, applied mathematics and biochemistry.

• Miguel Bernabeu – University of Edinburgh
• Ioanna Manolopoulou – University College London
• Niels Peek – University of Manchester
• Iain Styles – Queen’s University Belfast
• Paul Taylor – University College London
• Catalina Vallejos – University of Edinburgh
• Angela Wood – University of Cambridge
• David Wong – University of Manchester
• Tom Nichols – University of Oxford
• Magnus Rattray – University of Manchester

Beyond Education. Experience.

Graduate programs.

• Professional Doctorate
• Certificate
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• Master’s Programs
• Certificate Programs
• Financial Aid
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Experiential Learning

Should I Go To Grad School: 4 Questions to Consider

Global Reach

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Admission Steps

Health informatics - health data utilization and analysis - ms, admission requirements.

Terms and Deadlines

Degree and GPA Requirements

Additional Standards for Non-Native English Speakers

Additional standards for international applicants.

For the 2024-2025 academic year

Fall 2024 quarter (beginning in September)

Final submission deadline: July 26, 2024

International submission deadline: May 6, 2024

Winter 2025 quarter (beginning in January)

Final submission deadline: November 22, 2024

International submission deadline: September 9, 2024

Spring 2025 quarter (beginning in March)

Final submission deadline: February 14, 2025

International submission deadline: December 9, 2024

Summer 2025 quarter (beginning in June)

Final submission deadline: May 2, 2025

International submission deadline: February 24, 2025

Final submission deadline: Applicants cannot submit applications after the final submission deadline.

Degrees and GPA Requirements

Bachelors degree: All graduate applicants must hold an earned baccalaureate from a regionally accredited college or university or the recognized equivalent from an international institution.

Grade point average: The minimum undergraduate GPA for admission consideration for graduate study at the University of Denver is a cumulative 2.5 on a 4.0 scale or a 2.5 on a 4.0 scale for the last 60 semester credits or 90 quarter credits (approximately two years of work) for the baccalaureate degree. An earned master’s degree or higher from a regionally accredited institution supersedes the minimum standards for the baccalaureate. For applicants with graduate coursework but who have not earned a master’s degree or higher, the GPA from the graduate work may be used to meet the requirement. The minimum GPA is a cumulative 3.0 on a 4.0 scale for all graduate coursework undertaken.

Program GPA requirement: The minimum undergraduate GPA for admission consideration for this program is a cumulative 2.5 on a 4.0 scale

Official scores from the Test of English as a Foreign Language (TOEFL), International English Language Testing System (IELTS), C1 Advanced or Duolingo English Test are required of all graduate applicants, regardless of citizenship status, whose native language is not English or who have been educated in countries where English is not the native language. Your TOEFL/IELTS/C1 Advanced/Duolingo English Test scores are valid for two years from the test date.

The minimum TOEFL/IELTS/C1 Advanced/Duolingo English Test score requirements for this degree program are:

Minimum TOEFL Score (Internet-based test): 80 with minimum of 20 on each subscore

Minimum IELTS Score: 605 with minimum of 6.0 on each band score

Minimum C1 Advanced Score: 176

Minimum Duolingo English Test Score: 115 with a subscore minimum of 105 for Literacy, Comprehension, and Conversation and minimum subscore of 95 for Production

English Conditional Acceptance Offered: No, this program does not offer English Conditional Admission.

Read the English Language Proficiency policy for more details.

Read the Required Tests for GTA Eligibility policy for more details.

Per Student & Exchange Visitor Program (SEVP) regulation, international applicants must meet all standards for admission before an I-20 or DS-2019 is issued, [per U.S. Federal Register: 8 CFR § 214.3(k)] or is academically eligible for admission and is admitted [per 22 C.F.R. §62]. Read the Additional Standards For International Applicants policy for more details.

Application Materials

Transcripts, letters of recommendation.

Required Essays and Statements

We require a scanned copy of your transcripts from every college or university you have attended. Scanned copies must be clearly legible and sized to print on standard 8½-by-11-inch paper. Transcripts that do not show degrees awarded must also be accompanied by a scanned copy of the diploma or degree certificate. If your academic transcripts were issued in a language other than English, both the original documents and certified English translations are required.

Transcripts and proof of degree documents for postsecondary degrees earned from institutions outside of the United States will be released to a third-party international credential evaluator to assess U.S. education system equivalencies. Beginning July 2023, a non-refundable fee for this service will be required before the application is processed.

Upon admission to the University of Denver, official transcripts will be required from each institution attended.

Recommendations are optional and not required as part of admission materials. The admission committee reserves the right to request recommendations when reviewing an admission application.

Essays and Statements

Personal statement instructions.

At University College, we strive to foster a collaborative and engaging learning environment that emphasizes the practical application of knowledge and supports self-directed, motivated learners. Our programs are designed to build upon the unique background and experiences of adult learners.   A personal statement (two pages double-spaced, 450-500 words) is required and should be submitted via the application status page. In your personal statement please answer the following questions: 1. How does your chosen program/concentration align with your personal and professional goals? 2. In what ways will your work experiences, professional background, previous education, or other lived experiences enable you to contribute to an engaging learning environment?

Résumé Instructions

The résumé (or C.V.) should include work experience, research, and/or volunteer work.

Start the Application

Online Application

Financial Aid Information

Start your application.

Your submitted materials will be reviewed once all materials and application fees have been received.

Our program can only consider your application for admission if our Office of Graduate Education has received all your online materials and supplemental materials by our application deadline.

Application Fee: $75.00 Application Fee

International Degree Evaluation Fee: $50.00 Evaluation Fee for degrees (bachelor's or higher) earned from institutions outside the United States.

Applicants should complete their Free Application for Federal Student Aid (FAFSA) by February 15. Visit the Office of Financial Aid for additional information.

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• About PHIFP
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Data Science Upskilling (DSU) Program

• The Data Science Upskilling (DSU) program strengthens skills in data science, analytics, modeling, and informatics and advances the workforce at CDC.
• DSU supports CDC’s Data Modernization Initiative by improving data science capacity and capabilities of the CDC workforce.

The Data Science Upskilling (DSU) program helps CDC employees build foundational data science skills and access the tools to create and share modern, integrated, and high-quality information that protects the nation's health.

CDC staff and fellows learn and apply skills through this 10-month team-and project-based training opportunity. DSU strengthens skills in data science, analytics, modeling, and informatics and advances the development of a state-of-the-art workforce at CDC.

How DSU Works

First year CDC Public Health Informatics Fellowship Program fellows are automatically enrolled in the DSU program.

CDC employees and fellows self-form teams to apply for participation in DSU and receive technical support on projects. Each team applies by submitting a proposed data science project that is important to their work and aligned with CDC priorities (e.g., CDC's Data Modernization Initiative, emergency response-related events). Teams accepted into DSU learn directly from data science experts, receive support from peers and a learning community, and use curated online learning resources.

Program activities include:

• Skill-building training and curriculum,
• Team project-based learning, and
• Technical advising within a learning community.

DSU is designed to apply adult learning principles to maximize learning. Learners bring their center, institute, or office (CIO) projects to DSU so they can apply their data science training directly to their work. This experiential learning and knowledge sharing approach has an immediate benefit for DSU learners, their CIOs, and the agency as a whole.

Impact on Data Modernization

The DSU program supports CDC's Public Health Data Modernization Initiative by improving the data science capacity and capabilities of the CDC workforce.

The program grew 176% from 13 teams in 2019 (when the program started) to 36 teams 2022. Over these 4 years, DSU upskilled more than 360 individual learners in data science. The expected long-term impact of DSU is advancement of CDC's mission by supporting rapid identification and mitigation of emerging health threats and collecting and analyzing trusted data to promote evidence-based behaviors, interventions, and solutions to protect health, and preparing the CDC workforce to face the public health challenges of the future.

Although DSU has existed for 5 years, the program has more than exceeded its goals. It has trained diverse talent throughout CDC, including epidemiologists, behavioral scientists, medical officers, laboratorians, and fellows. Annual evaluation results indicate a high level of engagement; teams reported that DSU improved their data science knowledge and skills and their confidence in making data science decisions. A majority of DSU alumni reported continued use of acquired skills after program completion.

Advancing Data Science in the Federal Public Health Workforce‎

Learn more on how DSU is Bolstering Data Science Expertise at the U.S. Centers for Disease Control and Prevention (CDC) .

Journal of Public Health Mangement and Practice , March/April 2024.

DSU in the News

The Emergence of Citizen Data Scientists: A New Frontier in Business Analytics

The rise of the citizen data scientist ― employees who have been trained to handle data tasks in-house ― addresses the shortage of trained data scientists and the need for affordable business analytics. With advancing technology, there is a growing demand for citizen data scientists who can use advanced analytic tools effectively. Initiatives like CDC's Data Science Upskilling program demonstrate successful efforts to train people in technical and non-technical data literacy skills, which are critical in today's data-driven world.

Breaking News Network

February 1, 2024

Who to contact

For more information on the DSU program, please send an email to [email protected] .

• Public Health Infrastructure Center
• Division of Workforce Development

Public Health Informatics Fellowship Program (PHIFP)

The Public Health Informatics Fellowship Program (PHIFP) is a 2-year paid fellowship to apply information science and technology to the practice of public health.

Online introductory R courses for environmental health data science skills

• Practitioners, professionals, or researchers in the environmental health space who want programming and data science skills.
• Educators who want programming and data science skills with a focus on environmental health
• Practitioners, professionals, researchers, or advanced students from Minority Serving Institutions or institutions without training opportunities like DaSEH.

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