Florida State University

What you'll study

The PhD programme combines rigorous coursework in probability and statistical theory with applied training in biostatistical methods. Early coursework typically covers probability theory, mathematical statistics, linear models, and computational statistics. Core biostatistics topics and elective modules commonly include survival analysis, longitudinal and clustered data analysis, generalized linear mixed models, clinical trials design and analysis, causal inference for observational studies, Bayesian methods, high-dimensional data analysis, and statistical genomics.

Students also gain practical experience through applied projects and practicum courses that involve collaboration with biomedical investigators. Training emphasises modern computing and software development for reproducible research, using tools such as R and other scientific computing environments. The programme culminates in independent dissertation research under the supervision of a faculty adviser, and students normally complete qualifying examinations and a dissertation defence.

Entry requirements

Applicants are expected to have a strong quantitative background, normally demonstrated by an undergraduate or master’s degree in statistics, mathematics, biostatistics, or a closely related field. Typical preparation includes courses in multivariable calculus, linear algebra, probability, and mathematical statistics; background in statistical computing is strongly recommended.

Application materials usually include academic transcripts, a statement of purpose describing research interests (especially in biostatistics), a CV, and letters of recommendation from academic or professional referees. International applicants must demonstrate English language proficiency according to the university’s requirements. Prospective applicants should consult the department for current guidance on test requirements; some applicants may submit standardised test scores if requested or if they wish to supplement their application.

Admission is competitive and research fit with faculty is an important consideration. Many admitted students enter with funding in the form of graduate assistantships or fellowships; prospective applicants should review funding opportunities and contact potential faculty advisers to discuss research alignment.

Career prospects

Graduates of the PhD in Statistics with a biostatistics focus follow diverse career paths. Common destinations include tenure-track academic positions in statistics or biostatistics, research scientist roles in pharmaceutical and biotechnology companies, methodological and applied positions in contract research organisations, and analytic positions in public-health agencies or regulatory bodies. Other common roles include clinical trials statistician, statistical geneticist, data scientist in health tech, and consultant for healthcare analytics.

The combination of strong theoretical training and applied experience prepares graduates to lead collaborative research teams, design and analyse clinical studies, develop new statistical methodology for complex biomedical data, and contribute to interdisciplinary translational research initiatives.

Why study at Florida State University

Florida State University offers a PhD environment with close faculty mentorship and opportunities for interdisciplinary collaboration across the university’s biomedical and public-health units. Students benefit from access to research partnerships with the College of Medicine, public-health researchers, and regional healthcare organisations, enabling applied projects and data-driven dissertation work.

The Department of Statistics provides strengths in both theoretical and computational statistics, with faculty working on methodological problems directly relevant to biomedical research, such as longitudinal modelling, survival analysis, Bayesian computation and high-dimensional inference. Doctoral students receive professional training through teaching and presentation opportunities, access to research computing resources, and a network that supports placement in academic and applied research careers.