Medical Statistics and Health Data Science

Entry requirements

An upper second-class honours degree or international equivalent in a subject with a strong quantitative element. Including, but not limited to, degrees in: Mathematics, Statistics, Physics, Computer Science, Operational Research, Electrical and electronic engineering, Economics, Accounting, Aerospace Engineering, Data Science, Computing, Operations Research, Econometrics, Astro Physics, Mechanical Engineering, Aeronautical Engineering, Systems Engineering, Electronic Engineering, Electrical Engineering, Nuclear Engineering. Joint-honours involving those degree topics (e.g. ‘Physics and French” or “Economics and History” are also acceptable.)

Degrees should contain a minimum of three quantitative modules at 2:1/60% or international equivalent, such as: Algebra, Calculus, Financial Maths, Maths, Pure Maths, Business Mathematics, Business Statistics, Computer Science (including programming/algorithms), Data Mining/Data Science/ Data Analytics, Econometrics, Financial Modelling, Probability, Quantitative Methods, Quantitative Research Methods, Statistics/Statistical Methods/Statistical Analysis etc., Cost Analysis, Decision Analysis and Simulation, Economics, Financial Analysis, Game Theory, Macroeconomics, Microeconomics, Engineering Maths.

For applicants who are currently completing a degree, we understand that their final grade may be higher than the interim grades or module/unit grades they achieve during their studies.

We will consider applicants whose interim grades are currently slightly lower than the programme's entry requirements. We may make these applicants an aspirational offer. This offer would be at the standard level, so the applicant would need to achieve the standard entry requirements by the end of their degree. Specific module requirements may still apply.

We will consider applicants whose grades are slightly lower than the programme's entry requirements, if they have at least one of the following:

• evidence of significant, relevant work experience (such as a statistician or quantitative analyst (University or industry), quantitative researcher, a job in accounting, finance or actuarial science or as a computer programmer.
• a relevant postgraduate qualification.

If this is the case, applicants should include their CV (curriculum vitae / résumé) when they apply, showing details of their relevant work experience and/or qualifications.

See international equivalent qualifications on the International Office website.

Months of entry

September

Course content

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 high-quality training in statistical and computational methods that are applicable to low-, middle- and high-income settings.

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 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. All 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 spanning the design of randomised trials, statistical methods and data science approaches, you will benefit from this established expertise as a student on the MSc.

Information for international students

See international equivalent qualifications on the International Office website.

Fees and funding

HDR UK offer scholarships of £10,000 for home students. Find more information on the HDR UK website.

The University of Bristol Opportunity Bristol scheme offers scholarships (fees and living costs) for UK nationals with home fee status from Black backgrounds.

NIHR pre-doctoral fellowships offer up to two years funding including salary and tuition fees.

Further information on funding for prospective UK and international postgraduate students.