Rice University

What you'll study

The programme combines rigorous core training in probability, statistical theory and computational methods with specialised coursework and research in biostatistics. Early coursework typically covers probability theory, statistical inference, linear and generalized linear models, and computational statistics. Advanced and elective topics commonly include survival analysis, longitudinal and correlated data, causal inference, high-dimensional statistics, Bayesian methods, statistical genomics, clinical-trial design, and modern machine‑learning techniques for biological data.

Students progress from coursework to independent research: they complete a qualifying examination or equivalent assessment, undertake advanced seminars, participate in collaborative projects and typically serve as teaching assistants. Research often involves partnerships with clinicians and researchers across the Texas Medical Center and Rice’s interdisciplinary centres, allowing students to work on real-world datasets from areas such as genomics, epidemiology, imaging and translational medicine. The degree culminates in an original dissertation that contributes new methods or substantive applications in biostatistics.

Entry requirements

Applicants are expected to have a strong quantitative background, normally evidenced by an undergraduate degree in statistics, mathematics, biostatistics, computer science or a closely related field. Key preparation includes coursework in calculus, linear algebra, probability, mathematical statistics and some programming experience (for example in R, Python or C++). Relevant research or applied experience in statistics, bioinformatics or biomedical research is highly desirable.

Application materials typically include official transcripts, a statement of purpose describing research interests, letters of recommendation, and a curriculum vitae. Some applicants enter with a master’s degree in a related field, while others proceed directly from undergraduate study; admissions decisions weigh the overall strength of quantitative preparation and research potential. Applicants whose first language is not English should provide evidence of English proficiency as required by the university.

Career prospects

Graduates are prepared for careers in academic research and teaching, as well as leadership roles in industry and the public sector. Common destinations include university faculty positions in statistics and biostatistics, research scientist roles in pharmaceutical and biotechnology companies, positions in clinical trials and regulatory science, and data-science roles in healthcare organisations and government agencies. Graduates also work in translational research groups, public-health agencies, medical centres and start-ups focused on precision medicine and computational biology.

Why study at Rice University

Rice offers a collaborative environment with a favourable student-to-faculty ratio and strong opportunities for cross-disciplinary work. The Department of Statistics is embedded in a research ecosystem that includes close links to the Texas Medical Center, neighbouring research hospitals and Rice’s centres for computational and biomedical research. Students benefit from access to clinical collaborators, large biomedical datasets and advanced computing infrastructure.

Rice’s emphasis on mentorship and interdisciplinary training helps students translate methodological advances into impactful applied projects. The university’s location in Houston provides a broad professional network across academia, healthcare and industry, supporting internships, postdoctoral appointments and long‑term career connections.