University of Michigan

What you'll study

The programme combines rigorous coursework in probability and statistical inference with applied biostatistical methods and computational training. Core subjects typically cover probability theory, statistical inference, linear models and regression, and computational statistics. Biostatistics-focused modules include survival analysis, longitudinal data analysis, design and analysis of clinical trials, categorical data methods, and causal inference. Electives allow specialisation in areas such as statistical genetics, high-dimensional data, Bayesian methods, and machine learning for biomedical data.

Students normally complete a sequence of core courses followed by electives and an applied component. The applied component can take the form of a practicum or capstone project conducted in collaboration with faculty in the Department of Biostatistics, School of Public Health, or with clinical and research partners across the university. Coursework emphasises reproducible data analysis, statistical computing (R, Python and specialised software), study design and interpretation of results for biomedical audiences.

Entry requirements

Applicants are expected to hold a bachelor’s degree in statistics, mathematics, biostatistics, computer science, engineering, or a closely related discipline. Strong preparation in calculus, linear algebra, probability and introductory statistics is required. Successful applicants typically demonstrate quantitative coursework, programming experience, and substantive interest in biological or medical problems. Academic transcripts, a statement of purpose describing research or applied interests, and letters of recommendation are required. Admissions committees also consider relevant research experience, internships or work experience in a quantitative role. International applicants must meet the university’s English language proficiency expectations.

Career prospects

Graduates enter a range of careers across academia, industry and public sector organisations. Common roles include biostatistician or statistical programmer in pharmaceutical and biotechnology companies, clinical trials statistician, data scientist in health-technology firms, public health analyst, and research statistician in academic medical centres. Alumni also pursue doctoral study in biostatistics, statistics or related fields. The programme’s applied projects and connections to clinical researchers and industry partners provide routes into internships and positions in hospitals, research institutes, regulatory agencies and contract research organisations.

Why study at University of Michigan

The University of Michigan offers a multidisciplinary environment with active collaboration between the Department of Statistics and the School of Public Health’s Department of Biostatistics, enabling access to biomedical research, clinical collaborators and extensive datasets. Students benefit from a strong research culture, opportunities for applied practicum placements with medical and industry partners, and access to seminars and workshops led by internationally recognised faculty. The campus also provides career services, a broad alumni network in health and life sciences, and resources for students pursuing both professional practice and further academic study.