University of Leicester

What you'll study

The programme blends taught modules with an independent research project. Core themes include programming for bioinformatics (Python and R), statistics and machine learning for biological data, sequence analysis and genomics, transcriptomics and functional genomics, proteomics and structural bioinformatics, and database design and management for biological datasets. Teaching methods typically include lectures, hands-on computer laboratories, seminars and a substantial individual research project that gives experience of designing and executing a bioinformatics investigation from data acquisition to interpretation.

• Programming and Data Analysis: practical training in scripting, data wrangling, reproducible workflows, and use of common bioinformatics libraries and tools.
• Genomics and NGS Data: analysis of high-throughput sequencing data, variant calling, genome assembly and annotation, and comparative genomics.
• Statistics & Machine Learning: applied statistical methods for experimental design and analysis, plus supervised and unsupervised learning approaches used in biological datasets.
• Proteomics & Structural Biology: peptide identification, mass-spectrometry data processing, and basics of protein structure analysis.
• Databases & Pipelines: relational and non-relational biological databases, data integration and scalable pipeline development, including use of high-performance computing resources.
• Research Project: a major independent project supervised by university researchers that applies computational methods to a current biological problem and culminates in a written dissertation and oral presentation.

Entry requirements

Applicants are normally expected to hold a UK upper second-class (2:1) honours degree, or an international equivalent, in a relevant subject such as biology, genetics, computer science, mathematics, statistics, or a closely related discipline. Candidates with a lower second-class degree and strong relevant experience, or with significant professional experience in bioinformatics or computational biology, may also be considered. Practical experience in programming (for example Python or R) and a grounding in statistics is advantageous. All applicants whose first language is not English will need to meet the university's English language requirements.

Career prospects

Graduates develop transferable computational and analytical skills that are in demand across academia, industry and healthcare. Typical roles include bioinformatician, genomic data analyst, computational biologist, biostatistician, and data scientist within pharmaceutical companies, biotechnology firms, contract research organisations, public-sector research institutes and hospital laboratories. The course also provides a strong foundation for doctoral research for those wishing to continue in academic research or specialised technical roles in genomics and precision medicine.

Why study at University of Leicester

The University of Leicester offers research-led teaching with staff who are active in genomic and computational biology research, providing access to current methods and real-world datasets. Students benefit from practical training on industry-standard tools and access to the university's computing facilities for large-scale data analysis. The campus fosters interdisciplinary collaboration with biological scientists, statisticians and computer scientists, and there are opportunities to engage with collaborative projects and external partners including healthcare and industry contacts. The university’s careers and employability services also support students with career planning, placements and developing the professional skills needed to transition into bioinformatics roles.