University of Leicester

What you'll study

This programme combines core modules in programming, statistics and machine learning with health‑focused topics such as biostatistics, health informatics and the governance of health data. Teaching covers practical skills in Python/R, data cleaning and integration, feature engineering, supervised and unsupervised learning, time‑series and longitudinal analysis, causal inference methods, and reproducible research workflows.

Typical module themes include:

• Foundations of Computational Health Data Science – programming for health data, data structures and databases, and reproducible analysis.
• Statistical Methods and Biostatistics – regression, survival analysis, longitudinal models and interpretation for clinical research.
• Machine Learning for Health – classification, clustering, model evaluation, interpretability and applications to imaging or electronic health records.
• Health Informatics and Data Engineering – clinical data standards, data integration from multiple sources, HL7/FHIR concepts and scalable data pipelines.
• Ethics, Governance and Regulation of Health Data – data protection, anonymisation, consent, public and patient involvement, and regulatory frameworks relevant to health research.
• Research Project / Dissertation – an independent research project, often undertaken with datasets from clinical partners or public health repositories, where you apply learned methods to a substantive problem and produce a written dissertation.

The programme balances lectures, hands‑on practicals and project work. Assessments typically include coursework, practical coding assignments, group work, examinations and a substantial dissertation project.

Entry requirements

Applicants are normally expected to hold a good undergraduate degree (equivalent to a UK upper second class honours, 2:1) in a relevant subject such as computer science, statistics, mathematics, bioinformatics, physics, engineering, or a quantitative life‑science degree. Demonstrable experience in programming (for example Python or R), basic statistics and experience handling data will strengthen an application.

Applicants with a lower 2:2 plus significant relevant professional experience or strong quantitative skills may be considered. International applicants whose first language is not English will need to meet the University’s English language requirements (for example an approved level in IELTS or equivalent).

Selection considers your academic transcript, personal statement, references and where applicable relevant work or research experience. Applicants may be asked to provide a portfolio of coding or data projects.

Career prospects

Graduates move into roles across the health, clinical research and life‑science sectors. Typical job titles include clinical data scientist, health data analyst, biomedical data scientist, bioinformatics analyst, health informatics specialist, and machine learning engineer for healthcare. Employers include NHS trusts and clinical commissioning groups, pharmaceutical and biotechnology companies, medical technology firms, public health agencies, research institutes and commercial analytics consultancies.

The course also provides a route into doctoral research for students interested in academic careers. Training in governance and ethics additionally prepares students for roles where secure and ethical handling of patient data is required.

Why study at University of Leicester

The University of Leicester offers interdisciplinary teaching that links data science with health and biomedical research. The programme benefits from the University’s established strengths in computational methods and collaborations with local clinical partners, providing access to real‑world health datasets and applied project opportunities.

Students are taught by staff with expertise across statistics, machine learning and applied health research and have access to computing facilities, dedicated lab space for practical sessions, and careers support to connect with employers in the NHS and industry. The city of Leicester provides a supportive environment with strong community and public‑sector links, making it a practical base for students seeking experience in applied health data work.