The PhD program in Population Health Sciences prepares students to be leading researchers in population health sciences: an emerging interdisciplinary scientific field that aims to improve population health by addressing the multiple determinants of health and health disparities across populations and seeks to improve healthcare delivery.
Our students are trained to investigate the social, behavioral, and biological determinants of health through measurement, design and evaluation of research studies that address the critical issues in health outcomes and delivery of healthcare services across diverse populations. Students receive didactic interdisciplinary training in biostatistics, data science, epidemiology, health informatics, and health policy and economics, as well as principles of population health sciences. Students also receive hands-on training in state-of-the-art data science methodologies such as machine learning that prepare students with cutting-edge tools to solve complex population health challenges.
Featuring a partnership between Weill Cornell’s Department of Population Health Sciences and the Population Sciences Research Program of Memorial Sloan Kettering Cancer Center (MSK), our students have the opportunity to work with internationally renowned and federally funded faculty in multiple areas including biostatistics & data science, epidemiology, health informatics, health policy & economics, outcomes research, and behavioral sciences; addressing multiple determinants of health and health disparities across populations and improving healthcare delivery are cross-cutting themes within these disciplines.
Graduates of the program are positioned for research careers in population health sciences, including postdoctoral positions and tenure-track faculty positions in population health at schools of medicine, public health, and public policy across the country. Population health scientists are also actively recruited by industry, including pharmaceutical, technology and consulting firms, as well as by governmental agencies, such as the National Institutes of Health (NIH), Centers for Disease Control and Prevention (CDC) and the US Food and Drug Administration (FDA).
Applicants to the program are expected to have a minimum of a bachelor’s degree, strong academic record, demonstrated research interest aligning with faculty members, and prerequisite coursework in statistics, calculus, and at least one computer programming or statistical programming language such as R, Python, or SAS. Candidates must apply for admission online.
Successful applicants will likely have a background in one of the following data-driven disciplines:
- Public Health
- Statistics or biostatistics
- Health or biomedical informatics
- Health policy
- Computer science
- Industrial engineering or operations research
- Quantitative social sciences such as sociology
- Medical, genetics or natural sciences
Application materials will include academic transcripts from all post-secondary education, three letters of recommendation, CV/resume, and statement of purpose. Applicants are not required to take the General Graduate Record Examination (GRE exam). International Students who have not completed an academic degree in an English-speaking institution are required to take an English language proficiency exam. Applicants can demonstrate English Language proficiency using IELTS Academic, TOEFL iBT scores.
Applications for Fall 2024 is now open. The application deadline is December 1, 2023.
Becoming a Doctoral Candidate
In years one and two, students are required to complete required core coursework, participate in a credit-bearing colloquium, complete elective courses, and prepare for and complete their admission to candidacy exam (ACE). Students with advanced degrees may be able to complete the ACE after one year. Students will complete at least one 3-credit-hour research rotation directed by a faculty member before beginning their dissertation research, and can take up to 3 research rotations (9-credit hours) as appropriate. These research rotations will provide students an opportunity to broaden their understanding of population health sciences by participating in ongoing faculty research projects or completing an independent project under the guidance of a faculty member.
Students in the program take core and elective courses in their first two years of program. The core coursework includes:
- Biostatistics I with R Lab
- Biostatistics II - Regression Analysis
- Data Science I
- Data Science II
- Principles of Population Health Sciences
- Advanced Epidemiological Methods
- Introduction to Health Services Research
- Introduction to Health Informatics
- Responsible Conduct of Research
- PHS Colloquium series
Students are also required to take 7 elective courses, selected from existing WCGS advanced graduate coursework in biostatistics and data science (including artificial intelligence), health informatics, health policy and economics (including comparative effectiveness), and in computational biology.
PhD Research and Degree
Before beginning their dissertation research, each student will form a dissertation committee with a primary dissertation advisor and at least 3 internal committee members. The dissertation committee will evaluate the student's progress towards their dissertation every year during the dissertation phase.
The culmination of the student's successful progression through the program is the final examination (the "defense") and certification by the dissertation committee that the dissertation satisfies the requirements of the Graduate School for a PhD degree. Students are expected to complete this degree within five years of entering the program.
Bruce Schackman, PhD, MBA - Program Co-Chair
Jonine Bernstein, PhD, MS - Program Co-Chair
Samprit Banerjee, PhD, MS - Faculty Director
Elisabeth Brodbeck, PhD, MPH - Executive Director