Colorado State University

What you'll study

This PhD emphasises rigorous theoretical foundations in probability and statistical inference together with applied and computational methods used in modern biostatistics. Core study areas include advanced probability theory, mathematical statistics, linear and generalized linear models, mixed effects models, survival analysis, longitudinal data analysis, categorical data methods and nonparametric techniques.

Applied and computational modules commonly taken or researched by students include statistical computing and programming (R, Python and high-performance computing), Bayesian methods, causal inference, design and analysis of clinical trials, high-dimensional data analysis and genomics/bioinformatics methods. Students also pursue seminars in specialised topics such as spatial statistics, functional data analysis, adaptive designs and methods for environmental and veterinary data when these align with their research interests.

Programme structure combines coursework, qualifying examinations, teaching or research assistantships, and an independent dissertation. Early years typically focus on coursework and core examinations to build theoretical and computational competence, while later years concentrate on research projects done under the supervision of a faculty advisor. Collaborative projects with clinical, veterinary, agricultural and environmental researchers are a common feature.

Entry requirements

Applicants should hold a strong undergraduate or master's degree in statistics, biostatistics, mathematics, or a closely related quantitative discipline. Demonstrated competence in calculus, linear algebra, probability and mathematical statistics is expected. Practical experience with statistical computing and programming is highly desirable.

• Academic transcripts: evidence of strong quantitative coursework and high academic performance.
• Research experience: prior independent research, a master’s thesis or relevant applied projects strengthen an application.
• References: two or three academic or professional references who can speak to research potential and quantitative skills.
• Statement of purpose: clear research interests, fit with faculty and explanation of career goals.
• Additional materials: a CV and, for international applicants, proof of English language proficiency where required.

Admission is competitive and research fit with potential advisors is an important factor. Many admitted students hold funded assistantships or fellowships; prospective applicants are encouraged to contact potential faculty mentors about shared research interests before applying.

Career prospects

Graduates of this PhD go on to careers in academic research and teaching, public health agencies, pharmaceutical and biotechnology companies, clinical research organisations, government statistics and regulatory bodies, and private-sector analytics and consulting firms. Specific roles commonly taken include university faculty, biostatistician on clinical trials teams, quantitative scientist in biotech, data scientist for health-related data, and statistical consultant for interdisciplinary research.

Because of Colorado State’s strengths in veterinary medicine, agricultural sciences and environmental research, graduates also find opportunities in animal health, agricultural research organisations and environmental monitoring agencies where biostatistical expertise is needed.

Why study at Colorado State University

Colorado State University offers a PhD environment with strong interdisciplinary connections across health sciences, veterinary medicine, agriculture and environmental research. The Department of Statistics provides faculty expertise spanning theoretical statistics, computational methods and applied biostatistics, enabling students to work on diverse real-world problems.

Students benefit from collaborative research opportunities on a research-intensive campus, access to modern computing resources and partnerships with clinical and field researchers. The university’s location in Fort Collins and proximity to a growing regional life-sciences and technology sector also supports internship and industry collaboration possibilities.

Finally, doctoral training at Colorado State emphasises mentorship, teaching experience and development of grant-writing and communication skills, preparing graduates for both academic and applied career pathways in biostatistics.