Biomedical Data and Artificial Intelligence

Entry requirements

Normally a 2:1 Honours degree or equivalent in a mathematics, science or engineering subject, with significant mathematics content.

Months of entry

September

Course content

• Develop skills in data science and AI motivated by current research in biology and medicine.
• Learn about mechanistic mathematical modelling and dynamical systems theory applied to biology, ecology, neuroscience, synthetic biology and medicine complemented by advanced data science methods.
• You’ll keep abreast of current research happening in this fast-moving field from a range of internal and guest speakers our regular seminar series.
• Become proficient in requisite computational tools and techniques with practical sessions including key industry-standard programming languages such as MATLAB and Python.
• Undertake an independent research project where you’ll explore your interests in greater depth, with the support of an academic, where you can focus on or contribute to current research.
• Interact with world-leading research groups at the Living Systems Institute and gain first-hand experience of interdisciplinary study, including performing biological experiments and analysing biological datasets.

Information for international students

International students need to show they have the required level of English language to study this course. The required test scores for this course fall under Profile B2. Please visit our English language requirements page to view the required test scores and equivalencies from your country.

Fees and funding

The University of Exeter has many different scholarships available to support your education, including £5 million in scholarships for international students applying to study with us in the 2025/26 academic year, such as our Exeter Excellence Scholarships*.

For more information on scholarships and other financial support, please visit our scholarships and bursaries page.

Please also see our guidance on essential documentation required for an initial decision on taught programme applications.