MSc Medical Statistics and Health Data Science

The MSc in Medical Statistics and Health Data Science will enable you to engage with the complex statistical and data science healthcare challenges facing the global community, providing exceptional training in statistical and computational methods. As a medical statistician or health data scientist you will play a vital role in improving the health of populations by conducting statistical research (such as designing clinical trials and epidemiological studies, analysing data and interpreting results) to advance medical knowledge, track or prevent diseases, and improve medications and treatments. Challenges have arisen over the last decade in the increasing availability of enormous datasets related to human health and healthcare. Health data science combines expertise in epidemiology and statistics with programming computer science skills to enable analysis of these very large and diverse datasets. You will be trained in the theory and practice of cutting-edge methods in medical statistics and health data science (for example: causal inference, advanced regression models, infectious disease data analysis and machine learning). Teaching will focus on building strong quantitative and computational skills, and effective interpretation and communication of research findings. Concepts, skills and tools are illustrated using real-life case studies and health-related data. You will gain professional skills such as teamwork, presentation skills, and writing for publication – essential for a successful medical statistician and health data scientist. Population Health Sciences is a leading centre for research, with numerous opportunities for PhD study and employment on research projects. Internationally recognised for excellence in the development and dissemination of research methodology such as methods for randomised trials and causal inference. You will benefit from this established expertise as a student on the MSc. This MSc has Royal Statistical Society (RSS) accreditation reflecting the high-quality teaching, learning and assessment within the programme.

Applicants will typically need an upper second-class honours degree or an international equivalent in Aeronautical Engineering, Aerospace Engineering, Astrophysics, Chemical Engineering, Computer Science, Computing, Data Science, Electrical Engineering, Electronic Engineering, Mathematics, Mechanical Engineering, Nuclear Engineering, Operational Research, Physics, Statistics, or Systems Engineering. OR If the degree subject is not listed above, applicants will typically need an upper second-class honours degree or an international equivalent, and they will also need: Either A-level Mathematics (or international equivalent) at grade A or above OR three quantitative modules at 60% or above (or an international equivalent), including Algebra, Calculus, Financial Maths, Maths, Pure Maths, Business Mathematics, Business Statistics, Econometrics, Financial Modelling, Probability, Quantitative Methods, Quantitative Research Methods, Statistics/Statistical Methods/Statistical Analysis, Cost Analysis, Decision Analysis and Simulation, Economics, Financial Analysis, Game Theory, Macroeconomics, Microeconomics, or Engineering Maths AND A-level Mathematics (or international equivalent) a grade C or above. Applications may still be considered if interim grades are currently slightly lower than the programme's entry requirements and may make an aspirational offer. This offer would be at the standard level, meaning applicants would need to achieve the standard entry requirements by the end of their degree, and specific module requirements would still apply. Applications may also be considered if the final overall achieved grade is slightly lower than the programme's entry requirement. If an achieved grade is lower than the entry requirements, the application may be more likely to receive an offer if the applicant has additional relevant work experience or qualifications.