Biomedical Data and Artificial Intelligence MSc draft

Program Overview

The MSc in Biomedical Data and AI at the University of Exeter combines data science, AI, and mathematical modelling to solve real-world challenges in biology and medicine. Students benefit from a research-led curriculum, interdisciplinary collaboration, and world-class facilities at the Living Systems Institute. Graduates are prepared for careers in the pharmaceutical industry, data analytics, and academia, with strong skills in data analysis, AI, and mathematical modeling.

Program Outline

Degree Overview:

• Objectives: 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.
• Program Description:
• Stay abreast of current research in this fast-moving field through a regular seminar series featuring internal and guest speakers.
• Become proficient in requisite computational tools and techniques with practical sessions including key industry-standard programming languages such as MATLAB and Python.
• 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.

Outline:

• Course Content:
• Compulsory Modules:
• MTHM021 Advanced Mathematics Project:
60 Credits
• MTHM007 Engaging with Research:
15 Credits
• MTH3006 Mathematical Biology and Ecology:
15 Credits
• MTHM009 Advanced Topics in Mathematical Biology:
15 Credits
• NSCM005 Mathematical Modelling in Biology and Medicine:
15 Credits
• MTHM015 AI and Data Science Methods for Life and Health Sciences:
15 Credits
• Optional Modules:
• Select 45 Credits from the following:
• MTHM017 Advanced Topics in Statistics:
15 Credits
• MTHM018 Dynamical Systems and Chaos:
15 Credits
• MTHM033 Statistical Modelling in Space and Time:
15 Credits
• MTHM503 Applications of Data Science and Statistics:
15 Credits
• MTH3039 Computational Nonlinear Dynamics:
15 Credits
• MTH3008 Partial Differential Equations:
15 Credits
• MTH3011 Nonlinear Systems and Control:
15 Credits
• MTH3024 Stochastic Processes:
15 Credits
• MTH3028 Statistical Inference: Theory and Practice:
15 Credits
• MTH3027 Special Topics in Statistics:
15 Credits
• MTH3049 An Introduction to Causal Inference:
15 Credits
• MTHM
NQF Level 7 modules in Mathematics: 15 Credits
• ECMM4
NQF Level 7 modules in Computer Science: 15 Credits
• MTH3
NQF Level 6 modules in Mathematics: 15 Credits
• Examples of Previous Projects:
• Computer-in-the-loop control of cellular population dynamics (Kyle Wedgwood)
• Pattern formation via long-range cell-to-cell contact: revisiting Turing's morphogenesis hypothesis (Kyle Wedgwood)
• Network modelling approaches to generating seizure onset patterns (Jen Creaser)
• Mathematical modelling and analysis of brain dynamics in mood disorders (Jen Creaser)
• Mathematical modelling and analysis of antibiotics uptake in gram negative bacteria and implications for antimicrobial resistance (Krasi Tsaneva-Atanasova)
• Mathematical modelling for precision medicine (Krasi Tsaneva-Atanasova)
• The nonlinear neural dynamics of synchronising to complex rhythms (James Rankin)
• The impact of hearing loss on language networks (James Rankin)
• A mathematical and computational framework for neurobiological modelling: Behaviour-driven optimisation of neural connectivity (Roman Borisyuk)
• What does that neuron do?
A study of the neural circuits that produce swimming in the tadpole (Roman Borisyuk)
• Dynamics of locomotion and phagocytosis in shape-changing cells: theory and experiments (Kirsty Wan)
• A novel opto-hydrodynamical platform for studying microorganism movement in three-dimensions (Kirsty Wan)
• Modelling convergent cell signalling pathways mediating the neurophysiological stress response (Jamie Walker)
• Modelling the relationship between ion channel expression and electrical activity in stress-sensitive cells (Jamie Walker)
• Linking models of large-scale brain networks with data to understand neurological disorders (Marc Goodfellow)
• Personalised brain models for the management of epilepsy (Marc Goodfellow)

Assessment:

• Modules: Assessed by coursework only, or a mixture of coursework and an exam.
• Project:
• Short initial report or project proposal of around 1,000 words.
• Public presentation.
• Dissertation of 10,000 to 20,000 words.
• Assessed by the supervisor and a second marker.

Teaching:

• Research-led Teaching: Taught by experts active in research and practice.
• Interdisciplinary Working: Encouraged through collaboration with experts in biology and medicine.
• Seminars: Discuss the latest ideas, research discoveries, and new technologies.
• Fieldwork: Active involvement in research projects.
• Industry Practitioners: Taught by leading industry practitioners.

Careers:

• Potential Career Paths:
• Pharmaceutical industry
• Healthcare providers
• Software engineering
• Data analytics
• Skills Acquired: Data science, AI, and mathematical modelling.
• Applicable Fields: Epidemiology, neuroscience, translational medicine, and synthetic biology.
• Further Study: PhD.
• Career Support: Dedicated Career Zone team provides career guidance, one-on-one support, industry contacts, training events, workshops, and lectures.

Other:

• University of Exeter: Encourages interdisciplinary working and has a growing team of researchers tackling important problems in the field.
• Living Systems Institute: World-leading research group that students interact with.
• Top 20 in the UK for Mathematics: Ranked 18th in the Complete University Guide 2025.
• Top 50 in the world for Mathematics and Computer Science research: CWTS Leiden Ranking 2023.
• Research Expertise: Climate modelling and statistics; control and dynamics; systems biology; astrophysical fluid flows and number theory.

2024/25 entry UK fees per year: £12,100 full-time International fees per year: £27,500 full-time