North Carolina State University

What you'll study

This master's programme blends core statistical theory with applied biostatistical methods and computing. Students typically complete a mixture of required core courses, biostatistics electives and a culminating project or thesis, with options to tailor coursework toward clinical trials, genomics, or longitudinal and survival analysis.

• Core statistical foundations: probability theory, mathematical statistics, and linear models.
• Applied biostatistics courses: regression for biomedical data, survival analysis, longitudinal data analysis, and the design and analysis of clinical trials.
• Computational and data methods: statistical computing in R and Python, simulation methods, and high-dimensional data analysis.
• Advanced topics / electives: Bayesian methods, mixed-effects models, bioinformatics/genomics, causal inference and reproducible research.
• Culminating experience: options commonly include a project-based practicum with a public-health or industry partner, an applied consulting practicum, or a supervised thesis for students interested in research pathways.

Entry requirements

Admissions seek applicants with a solid quantitative background. Typical expectations include:

• An undergraduate degree in statistics, mathematics, biostatistics, computer science, engineering or a closely related discipline.
• Preparatory coursework in calculus (including multivariable), linear algebra, probability and mathematical statistics; familiarity with basic programming or data analysis (for example R or Python) is strongly recommended.
• Academic transcripts demonstrating quantitative achievement, a statement of purpose describing research or applied interests, and academic or professional references (usually two or three letters).
• International applicants must meet English language proficiency requirements; specific test score policies are set by the university and may vary.
• Some applicants will have relevant research, internship or work experience in biomedical, public-health or industry settings; such experience strengthens an application but is not always required.

Career prospects

Graduates are prepared for a range of roles where statistical expertise in biological and health contexts is needed. Common career destinations include:

• Biostatistician or statistical programmer in pharmaceutical and biotech companies, contributing to clinical trial design and regulatory submissions.
• Analyst or researcher in public-health organisations, hospitals, and government agencies working on observational studies, surveillance and policy evaluation.
• Data scientist or quantitative analyst in healthcare technology firms and health-data startups, applying machine learning and analytics to biomedical data.
• Research/statistics positions in academic groups or research institutes, supporting clinical and translational research, or continuing to doctoral study in biostatistics or statistics.

Why study at North Carolina State University

North Carolina State University offers a strong, research-active Statistics department with close ties to the broader Research Triangle region, giving students access to collaborative projects across universities, healthcare systems and industry. The programme emphasises applied training and statistical computing, helping students build practical skills sought by employers in clinical trials, biotech and public health.

• Collaboration and internships: proximity to Research Triangle Park and partnerships with local research hospitals and companies create internship and practicum opportunities.
• Faculty and research strengths: faculty expertise spans theoretical statistics, computational methods and applied biostatistics, allowing students to pursue diverse elective topics and research projects.
• Computing and support: access to robust computing resources, statistical consulting centres and student support services for career development and professional placement.