Ph.D. in Biostatistics Admissions

Application

Applications to the Ph.D. in Biostatistics is through the Duke University Graduate School application website. There you will find instructions and the needed information to apply. The online application for the 2024 - 2025 program is open.

Graduate School Application 

Please note: Application materials emailed or mailed to individual faculty members will not be reviewed by our Admissions Committee.

Deadline

The due date for 2024 - 2025 application materials is December 2, 2024 for Fall Semester 2025. The Department matriculates Ph.D. students in the fall only.

Entrance Requirements 

When submitting an application, candidates are required to have the following:

  • A completed on-line 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 not required for students applying to the PhD in Biostatistics Program for Fall 2024 matriculation. Additional information about the Duke University Graduate School application may be found at the Graduate School application website.
  • Test of English as a Foreign Language (TOEFL) score (If applicable) or​ International English Language Testing System (IELTS) score (If applicable) or the Duolingo English Test score

Additional information about the Duke University Graduate School application may be found at the Graduate School application website.

Application Fee

The application fee is $95. 

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

International Fee Waivers:

International Application Fee Waivers

International applicants may be eligible for an application fee waiver. These waivers are limited, and requests will be considered from August 31, 2024, to October 31, 2024. Those granted waivers will be informed by Nov 11, 2024.  If you are granted a departmental fee waiver, you will enter that single-use code on the “Fee Waiver” page of the application.

International applicants requesting a fee waiver should include the following information:

1. A clear statement of need (socioeconomic, living in zone of violent conflict, or explicit personal hardship). Widespread socioeconomic need is indicated in countries with an IHDI value of less than 0.5 on the Inequality-Adjusted Human Development Index

2. A current CV. 

Please note that all submitted materials for admissions purposes are subject to verification.

Requests should be sent to: tasha.allison@duke.edu

Student Profile

Some of the traits associated with success in our program are problem definition, problem solving, quantitative thinking, critical thinking, communication, intellectual curiosity, and dedication.  Regarding training, a mathematical background is particularly important.

Students will need proficiency in both single-variate and multi-variate calculus and linear algebra.  Specifically, incoming students should have a working knowledge of:

  • Optimization of functions
  • Inverse functions
  • Sequences, series and convergence, Taylor series
  • Convergence of sequences of functions (pointwise, uniform, in measure)
  • Differentiation and integration of single- and multi-variate functions
  • Fubini's theorem
  • Fundamental theorem of calculus
  • Matrix algebra and vectors
  • Vector spaces, metric spaces, Hilbert spaces
  • Linear operators
  • Spectral theorem and diagonalization of matrices
  • Inner products, quadratic forms and projections

A course in real analysis is strongly recommended.  As curricula can vary, please note that a suitable course would cover the following (in addition to the usual topics in derivatives and integrals):

  • Real and complex number systems
  • Basic point-set topology (compactness, continuity, connectedness)
  • Metric spaces
  • Numerical sequences, convergence, Cauchy sequences
  • Sequences and series of functions

For an example text, please see Rudin's “Principles of Mathematical Analysis” (known as 'Baby Rudin').