Worcester Polytechnic Institute

What you'll study

The programme combines core computational and biological coursework with project‑based learning so students gain practical experience analysing real biological data. Core topics typically include:

• Foundations of molecular and cellular biology — sequence structure and function, gene expression, and laboratory methods at a conceptual level to enable computational interpretation.
• Algorithms and data structures for bioinformatics — sequence alignment, assembly, graph‑based methods and algorithmic complexity.
• Genomics and transcriptomics — next‑generation sequencing data analysis, variant calling, and comparative genomics approaches.
• Statistical methods and biostatistics — probability, hypothesis testing, regression, and designs for analysing high‑dimensional biological datasets.
• Machine learning and data mining — supervised and unsupervised techniques applied to omics, imaging and clinical datasets.
• Structural and systems bioinformatics — protein structure prediction, molecular modelling and network-based analysis of pathways and interactions.
• Software engineering and reproducible research — programming (Python, R or similar), version control, pipelines, and best practices for reproducible computational work.

Students choose between thesis or project options, completing an independent research project or practicum that typically involves collaboration with faculty, campus research centres or industry partners. Seminars and elective modules allow specialisation in areas such as computational genomics, biomedical data science, or imaging analysis.

Entry requirements

Applicants are normally expected to hold a bachelor’s degree in a relevant discipline such as biology, computer science, mathematics, statistics, engineering or a closely related field. Typical academic expectations include evidence of quantitative preparation (calculus, linear algebra, probability/statistics) and some programming experience. Where applicants come from primarily biological backgrounds they will usually need demonstrated competence in computing; conversely, applicants from computing or quantitative fields should show familiarity with core biological concepts.

Application materials commonly required are official transcripts, a personal statement describing research and career goals, letters of recommendation, and a CV. GRE requirements may vary and applicants should consult the department for current guidance. International applicants must meet English language proficiency requirements.

Career prospects

Graduates enter roles across biotechnology, pharmaceutical companies, healthcare organisations, academic and government research labs, and data‑intensive start‑ups. Typical job titles include bioinformatician, computational biologist, genomics analyst, data scientist, biostatistician and software developer for life‑science applications. The programme also prepares students for doctoral study in computational biology, genomics or related fields.

Graduates benefit from hands‑on project experience and the opportunity to collaborate with faculty on publishable research, which can be advantageous when seeking positions that require practical data analysis skills or when applying for PhD programmes.

Why study at Worcester Polytechnic Institute

Worcester Polytechnic Institute emphasises interdisciplinary, project‑based education that integrates computation with biological problems. Students have access to campus research groups and laboratories working on genomics, systems biology and bioengineering, and benefit from a culture of collaboration between computer science, biology and engineering faculty.

The programme’s focus on applied projects and capstone research connects students with local and regional biotechnology and healthcare organisations, providing opportunities for internships and collaborative research. Smaller class sizes and close faculty supervision mean students get mentoring on technical development, research design and professional preparation.