Harvey Mudd College

What you'll study

This programme integrates core courses from mathematics, computer science and biology to build fluency in modelling, data analysis and laboratory techniques. Typical areas of study include calculus and differential equations, linear algebra, probability and statistics, algorithms and data structures, molecular and cellular biology, genetics and genomics, and laboratory methods in biochemistry and molecular biology.

Coursework emphasises practised computational skills such as programming for data analysis, machine learning methods applied to biological datasets, sequence analysis, phylogenetics, and stochastic modelling of biological systems. Students also undertake collaborative projects that combine wet‑lab experiments with computational analysis, and are trained in reproducible workflows, data management and scientific communication.

The curriculum structure generally includes a sequence of foundational mathematics and programming courses in the first years, intermediate biological science and statistics courses, and advanced electives or seminars in topics such as systems biology, structural bioinformatics, computational genomics, and mathematical biology. A major component is an independent capstone or senior research project, often carried out under faculty supervision and frequently undertaken in collaboration with other Claremont Colleges, local research institutes, or industry partners.

Entry requirements

Admission to Harvey Mudd College is selective and based on a holistic review. Applicants to this major should demonstrate strong preparation in mathematics (including pre‑calculus and preferably some calculus), background in high‑school biology and chemistry, and evidence of quantitative reasoning and problem solving. Prior experience with programming or computational coursework is highly recommended but not strictly required.

Typical application materials include academic transcripts, teacher recommendations (including at least one from a mathematics or science instructor), personal essays that highlight interest in interdisciplinary quantitative work, and any relevant portfolios or project descriptions. Successful candidates show curiosity for research, resilience with challenging coursework, and readiness to engage in both laboratory and computational environments.

Career prospects

Graduates are well positioned for a range of paths at the interface of biology and computation. Common destinations include graduate study (PhD in computational biology, bioinformatics, statistics, applied mathematics or related fields), professional degrees in medicine or allied health, and research scientist roles in academia, government or industry. On the applied side, alumni work as bioinformatics analysts, computational biologists, data scientists, software engineers for biotech and health‑tech companies, and quantitative analysts in pharmaceutical development, genomics, and systems biology startups.

Students also move into roles in scientific consulting, regulatory science, science policy, and entrepreneurship. The programme’s strong emphasis on research, teamwork and communication equips graduates to translate quantitative results into biologically meaningful insights and to lead interdisciplinary projects.

Why study at Harvey Mudd College

Harvey Mudd combines a small liberal‑arts college environment with a STEM‑focused curriculum, giving students close faculty mentorship, small class sizes and extensive undergraduate research opportunities. The college’s collaborative culture and access to the other Claremont Colleges broaden course options and laboratory resources, allowing students to supplement their major with complementary coursework in chemistry, computer science, engineering or the social sciences.

Students benefit from a curriculum that emphasises hands‑on learning — from laboratory courses and computational practicums to a capstone research experience and the college’s project‑based Clinic model. Career services, strong industry connections in the Southern California biotechnology and data science communities, and active internship and research placements help translate academic training into professional opportunities.

Overall, Harvey Mudd is a strong choice for students seeking an intensive, interdisciplinary education in computational biology that combines rigorous quantitative training with practical laboratory and research experience.