Application
Applications to the Biostatistics PhD are submitted through the Duke University Graduate School application website. There you will find instructions and the needed information to apply. The online application for the 2025 - 2026 cycle is open.
Please note: Application materials emailed or mailed to individual faculty members will not be reviewed by our Admissions Committee.
Deadline
The Fall 2026 application deadline is December 1, 2025. The Department matriculates PhD students in the fall only.
Application Materials
When submitting an application, candidates are required to have the following:
- A completed online Graduate School application.
- Transcripts from all undergraduate and graduate institutions where you earned (or will earn) a degree, studied for one semester or more, or took classes that relate to your current application for graduate study.
- Three letters of recommendation.
- Statement of purpose.
- Graduate Record Examination (GRE) scores are optional.
- TOEFL, IELTS, or Duolingo English Test required for applications whose first language is not English (may be waived for some applicants).
- Optional: As part of your application, you may upload an optional summary of your undergraduate- and graduate-level mathematics and statistics coursework.
Additional information about the Duke University Graduate School application may be found at the Graduate School application website .
Application Fee
The application fee is $105.
The Graduate School provides a limited number of application fee waivers. Domestic applicants should use the following link regarding a request for a waiver: The Graduate School policy for fee waivers .
Prerequisites/Student Profile
Applicants to the Biostatistics PhD are expected to have strong quantitative preparation and a demonstrated interest in methodological research in biostatistics. Competitive candidates will have completed the following coursework before enrollment:
- Multivariate calculus
- At least one semester of linear algebra
- Probability and statistical inference at the level of an advanced undergraduate statistics curriculum
- Knowledge of a programming language such as R, Python, or SAS
A course in real analysis is strongly recommended. For an example text, please see Rudin's “Principles of Mathematical Analysis” (known as 'Baby Rudin').
In some cases, applicants who are outstanding overall but lack one of the listed prerequisites may still be admitted, with the expectation that they will complete the necessary coursework early in their doctoral studies.
Many successful applicants will have completed prior graduate training in biostatistics, statistics, or a related field, which can provide a strong foundation for doctoral study. Applicants holding only a bachelor’s degree may also be competitive if they demonstrate exceptional preparation and research potential.