Indiana University Bloomington

What you'll study

The programme combines core training in mathematics, statistics and computer science with specialised topics in molecular and systems biology. Core modules typically cover mathematical modelling of biological systems, statistical methods for high-throughput data, algorithms for sequence and structure analysis, machine learning for biological data, and programming for bioinformatics (commonly using R and Python).

Students also study subject-specific areas such as population and evolutionary genetics, transcriptomics and functional genomics, comparative genomics, structural bioinformatics, network and systems biology, and experimental design for omics studies. Practical components emphasise data analysis, reproducible computational workflows, and use of high-performance computing resources.

The degree is offered with flexible programme structures that generally include a mix of coursework and an independent research project or capstone. The project allows students to work with faculty on applied or theoretical problems, producing a thesis or substantial applied report. Elective options enable tailoring to interests in computational method development, translational bioinformatics, or quantitative systems modelling.

Entry requirements

Applicants should hold a recognised bachelor's degree in biology, mathematics, statistics, computer science, informatics, engineering or a closely related discipline. Strong quantitative preparation is expected, including coursework in calculus, linear algebra, probability/statistics and programming. Prior exposure to molecular biology or genetics is highly desirable for life-science-focused research tracks.

Typical application materials include official academic transcripts, a personal statement describing research interests and goals, two or three letters of recommendation, and a CV. Some applicants without formal bioinformatics coursework but with relevant research or programming experience may be admitted pending preparatory coursework. English language proficiency evidence is required for applicants whose first language is not English.

Career prospects

Graduates move into a range of roles across academia, industry and public sector organisations. Common career paths include computational biologist, bioinformatician, genomics data analyst, biostatistician, machine-learning scientist in biotech or pharmaceutical companies, and data scientist in healthcare or agricultural genomics.

Alumni also progress to doctoral study in computational biology, bioinformatics, biostatistics or related disciplines, or take research positions in university laboratories, national research institutes and contract research organisations. The quantitative and programming skills developed on the programme are also transferable to broader data science and analytics roles.

Why study at Indiana University Bloomington

Indiana University Bloomington offers a highly interdisciplinary environment, drawing on strengths in the School of Informatics, Computing, and Engineering, the Departments of Biology and Mathematics, and campus research centres focused on genomics and computational science. Students benefit from opportunities to collaborate with faculty across quantitative and life-science disciplines.

Pupils have access to robust computing infrastructure and research support, including campus high-performance computing facilities and shared bioinformatics resources. The campus also provides practical training through research labs and industry partnerships, plus career services and internship connections to help transition into research or industry roles.

Located in Bloomington, the university combines a research-focused academic setting with a supportive graduate community, making it a strong choice for students seeking rigorous interdisciplinary training in computational biology.