The Master of Biostatistics Program prepares students for success by combining rigorous academic training with hands-on research experience. While coursework provides a strong foundation in statistical theory, data analysis, and computational methods, applying those skills to real-world research questions truly prepares students for the next step in their careers.
Through the program's required master's project and additional research opportunities, students work with faculty investigators and multidisciplinary research teams to address complex biomedical and public health challenges. These experiences help students develop practical problem-solving skills, gain proficiency with real data, and understand how biostatistics contributes to scientific discovery.
Just as importantly, research experience serves as a powerful credential. Employers and doctoral admissions committees value applicants who have demonstrated their ability to contribute to meaningful research projects, collaborate with investigators, and communicate analytical findings effectively. For many students, research experience becomes a defining feature of their resume, graduate school application, or job search, and it provides the confidence to make an immediate impact in their next role.
Students have access to an extraordinary range of research opportunities across Duke University, Duke Health, and affiliated research centers. Faculty members in the Department of Biostatistics and Bioinformatics collaborate with investigators throughout the School of Medicine and beyond, creating opportunities for students to contribute to cutting-edge biomedical research.
Research projects span a wide variety of areas, including:
· Clinical trials and other designed experiments evaluating new treatments and interventions
· Genomics, precision medicine, and other high-dimensional biological data
· Analysis of electronic health records and large observational datasets
· Cancer, cardiovascular, neurological, and infectious disease research
· Population health, epidemiology, and health policy research
· Machine learning and artificial intelligence applications in healthcare
· Translational research that bridges scientific discovery and patient care
A distinguishing feature of the program is its emphasis on working with real data and addressing authentic scientific questions. Rather than learning through hypothetical examples alone, students contribute to ongoing research studies that have the potential to improve health outcomes, advance medical knowledge, and inform healthcare decisions.
Explore our student research stories to learn how Master of Biostatistics students are helping drive innovation across a broad range of disciplines.
Students are encouraged to explore research opportunities that align with their academic interests, career goals, and areas of curiosity. Each year, faculty members from the Department of Biostatistics and Bioinformatics and collaborating departments across Duke share project opportunities with students.
The process typically begins with students reviewing available projects and expressing interest in those that match their goals. Faculty mentors may meet with interested students to discuss the project, expectations, and desired skills before selecting team members. This process helps ensure a strong match between the student and the research experience.
For students with specialized interests, the program's faculty and leadership team can often facilitate introductions to investigators across Duke's extensive research community. Given the breadth of ongoing research throughout the School of Medicine and the university, there is no shortage of opportunities to find a project that is both intellectually engaging and professionally meaningful.
Whether your interests lie in clinical research, genomics, AI-driven healthcare, public health, or another area of biomedical science, the program offers a pathway to gain valuable research experience while building relationships with faculty mentors and research collaborators.
No. Students enter the program with a wide range of academic backgrounds and prior research experience. The curriculum is designed to help students develop the statistical, computational, and collaborative skills needed to succeed in research. Through coursework, mentorship, and hands-on project opportunities, students gain the experience and confidence necessary to contribute meaningfully to biomedical research regardless of their starting point.