University of Nottingham

What you'll study

This programme blends modules in computational methods, statistics and molecular biology to give practical competence in analysing genomic, transcriptomic, proteomic and other high-throughput datasets. Core topics typically include programming for bioinformatics (Python and/or R), statistical methods for biological data, next‑generation sequencing analysis, algorithms and data structures for biological problems, and introductions to population and functional genomics. You will also study advanced topics such as structural bioinformatics, systems and network biology, and machine learning applications in biology.

The course is delivered through a combination of lectures, hands‑on computer practicals, workshops and seminars. Assessment commonly involves coursework, practical reports, group work and written examinations. The programme culminates in an independent research project or dissertation, supervised by academic staff, where you apply bioinformatics techniques to a substantial real‑world problem, often using data from ongoing research groups or industrial collaborators.

Entry requirements

Typical entry is a good undergraduate degree (for example a 2:1 honours or equivalent) in a relevant discipline such as biological sciences, computer science, mathematics, statistics or a related subject. Applicants with a strong quantitative background but less formal biological training (or vice versa) are considered; you may be asked to demonstrate relevant programming experience or prior coursework in statistics/biology.

Applicants whose first language is not English will be required to meet the university's English language requirements. Professional experience in bioinformatics, laboratory research or software development can strengthen an application. Admission decisions take into account transcripts, references and the personal statement.

Career prospects

Graduates develop skills that are in demand across academia, healthcare and industry. Typical career paths include roles as bioinformaticians, computational biologists, genomic data analysts, biostatisticians, and software developers for life‑science applications. Employers include universities and research institutes, pharmaceutical and biotechnology companies, clinical genomics and diagnostics labs, agricultural and environmental organisations, and specialist bioinformatics service providers.

The degree also provides a solid foundation for doctoral study in bioinformatics, computational biology or related interdisciplinary fields for those pursuing a research career.

Why study at University of Nottingham

The University of Nottingham hosts active research groups working in computational biology, genomics and systems biology, providing opportunities for project collaborations and access to current datasets and expertise. Students benefit from taught modules designed and delivered by researchers with applied experience, as well as access to computing facilities and high‑performance computing resources used for large‑scale data analysis.

Interdisciplinary links across life sciences, computer science and statistics facilitate a broad training experience, and established partnerships with local and national industry increase opportunities for placements, project sponsorship and graduate employment. The campus environment supports postgraduate study with resources for skills development, seminars and networking with researchers and employers in the biosciences and bioinformatics sectors.