Unlike other programs which are tied to statistics, Harvard’s biostatistics program is specifically related to public health. The program has a rich history of innovation in addressing the greatest challenges in public health, biomedical research, computational biology, and now health data science. You will be joining a community of leading scientists and educators from around the world with easy access to Boston- and Cambridge-area hospitals such as Harvard Medical School, Dana-Farber Cancer Institute, Massachusetts General Hospital, and other world-class hospitals.

Current and former students are exploring important issues such as how biostatisticians play a critical role in discovering and developing medicine, using statistical methods in relation to electronic health records research, researching emotional and behavioral issues among youth born to women living with HIV, and working to understand the causes of long-term COVID.

Graduates of the program have secured faculty and research positions at diverse institutions such as Princeton University, Brown University, Liverpool School of Tropical Medicine, Stanford University, and the U.S. Military Academy at West Point. Others have gone into non-academic careers at organizations such as the HealthCore, Cerus Corporation, Bristol-Myers Squibb, RAND Corporation, the World Health Organization, and Genentech.

Additional information on the graduate program is available from the Department of Biostatistics and requirements for the degree are detailed in GSAS Policies.

Admissions Requirements

Please review GSAS admissions requirements and other information before applying. You can find degree program-specific admissions requirements below and access additional guidance on applying from the Department of Biostatistics.

Academic Background

Applicants must have successfully completed calculus through multivariable integration and one semester of linear algebra and have knowledge of a programming language. Candidates are also strongly encouraged to have:

  • Completed courses in probability, statistics, advanced calculus or real analysis, and numerical analysis
  • Practical knowledge of a statistical computing package such as SAS, Splus, R, Stata, or SPSS
  • Completed courses in biology, computational biology, and genetics (if interested in bioinformatics)
  • Knowledge of a scripting language such as Python or Perl and some familiarity with relational databases (if interested in bioinformatics)

From time to time the department will admit students to the program without this level of preparation with the understanding that the student will promptly make up any deficiencies, usually by taking additional courses prior to entering the program.

Theses & Dissertations

Theses & Dissertations for Biostatistics

Biostatistics Faculty