University of North Carolina at Chapel Hill

What you'll study

This programme blends core biology with rigorous quantitative and computational training. You will take foundational courses in cell and molecular biology, genetics and biochemistry alongside calculus, linear algebra, differential equations and probability. Core computational subjects include programming (commonly Python and R), data structures and algorithms, statistical inference and machine learning for biological data.

• Foundations in biology: molecular and cellular biology, genetics, laboratory techniques
• Mathematics and statistics: calculus sequence, linear algebra, differential equations, probability and statistical modelling
• Computer science and programming: introductory and intermediate programming, data structures, algorithm design, software development practices
• Specialist bioinformatics and computational courses: sequence analysis, comparative genomics, structural bioinformatics, systems biology, computational genomics, high‑throughput data analysis
• Practical training: laboratory classes, computing practicum, large‑data project work and a capstone research project or thesis with a faculty mentor
• Electives and interdisciplinary options: courses drawing on epidemiology, biostatistics, neuroscience, ecology or personalised medicine to tailor the degree to research or industry interests

The curriculum emphasises hands‑on data analysis, reproducible research practices, and experience with common bioinformatics tools and cloud or high‑performance computing environments. Many students undertake independent research, internships with industry or clinical research groups, and team projects that culminate in a capstone presentation or written thesis.

Entry requirements

Admission to UNC Chapel Hill is competitive and follows the university's undergraduate admissions process. Successful applicants typically present a strong high‑school record with emphasis on STEM courses. Recommended preparation includes calculus, chemistry and biology, and experience with programming or computer science is strongly beneficial.

• Academic preparation: strong performance in mathematics (including calculus), laboratory science (biology and chemistry), and coursework that develops quantitative reasoning
• Technical skills: prior exposure to programming, data analysis, or statistics is advantageous; many applicants strengthen their profile with coding projects, AP/IB courses, or summer STEM programmes
• Application materials: standard university application documentation, personal statement highlighting interest in computational biology, and letters of recommendation; transfer applicants should show university‑level coursework in relevant areas

Specific course prerequisites or recommended first‑year sequences may be required by the department; prospective students should consult UNC Chapel Hill admissions and the programme curriculum guide for details.

Career prospects

Graduates are equipped for roles that require both biological knowledge and quantitative/computational skills. Typical career paths include bioinformatician or computational biologist in academia, biotech and pharmaceutical companies, where work often focuses on genomics, drug discovery, or systems modelling.

• Research roles: research assistant or computational scientist in university labs, government research institutes or industry R&D teams
• Industry positions: bioinformatics analyst, data scientist, computational genomics specialist, clinical data analyst or software developer for life‑science tools
• Healthcare and public health: roles in clinical bioinformatics, health data analytics and epidemiological modelling
• Further study: many graduates progress to graduate programmes (MS/PhD) in computational biology, bioinformatics, biostatistics or related fields, and some pursue professional degrees such as MD/PhD

Internships, undergraduate research and collaborations with medical centres or industry partners are common routes to employment and graduate study opportunities.

Why study at University of North Carolina at Chapel Hill

UNC Chapel Hill offers an interdisciplinary research environment with strong links between the biological sciences, mathematics, statistics and computer science faculties. Students benefit from access to research centres and clinical partners on campus, opportunities for collaborative projects with the School of Medicine and specialised institutes, and proximity to the broader Research Triangle region.

• Research opportunities: plentiful undergraduate research placements and faculty‑led projects spanning basic and translational science
• Facilities and resources: laboratory facilities, computational infrastructure and training in high‑throughput data analysis
• Career support: dedicated advising, internship pipelines and connections with biotech, pharmaceuticals and public‑health employers
• Interdisciplinary community: a curriculum designed to bridge disciplines and prepare students for both academic and industry careers in computational biology

Overall, the programme prepares students to tackle contemporary biological questions with quantitative rigour and computational fluency, while providing pathways into research, industry and further study.