MSc Biomedical Data and Artificial Intelligence
| UCAS code | 1234 |
|---|---|
| Duration | 1 year full time |
| Entry year | 2026 |
| Campus | Streatham Campus |
| Typical offer | A 2:1 degree or equivalent |
|---|---|
Why study MSc Biomedical Data and Artificial Intelligence at Exeter?
- 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
Professor Krasimira Tsaneva Atanasova talks about Biomedical Data and Artificial Intelligence at the 樱花动漫. (This video refers to the mathematical modelling component of the course.)
Top 20 in the UK for Mathematics
20th in The Times and The Sunday Times Good University Guide 2026 and the
Top 10 in the world for our Mathematics and Computer Science research
CWTS Leiden Ranking 2024, by percent of articles in the top 10% most-cited
Wide range of exciting and high-impact research projects
Research expertise in mathematics for healthcare; systems biology; control and dynamics and computational neuroscience
Entry requirements
Normally a 2:1 Honours degree or equivalent in a mathematics, science or engineering subject, with significant mathematics content.
Requirements for international students
If you are an international student, please visit our international equivalency pages to enable you to see if your existing academic qualifications meet our entry requirements.
Please also see our guidance on essential documentation required for an initial decision on taught programme applications.
Entry requirements for international students
English language requirements
International students need to show they have the required level of English language to study this course.
The required IELTS test scores for this course fall under Profile B1.
Please visit our English language requirements page to view the required test scores and equivalencies from your country.
Course content
The modules below provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.
Please note that the module information displayed here is subject to change.
135 credits of compulsory modules, 45 credits of optional modules
You may select 15-45 credits form Optional Module Group 1
You may select 0-15 credits from Optional Module group 2
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| Compulsory 1 | ||
| Mathematical Biology and Ecology | 15 | |
| Advanced Topics in Mathematical and Computational Biology | 15 | |
| AI and Data Science Methods for Life and Health Sciences | 15 | |
| Advanced Mathematics Project | 60 | |
| Research in Mathematical Sciences | 15 | |
| Mathematical Modelling in Biology and Medicine | 15 | |
Optional modules
| Code | Module | Credits |
|---|---|---|
| Optional 1 | ||
| Methods for Stochastics and Finance | 15 | |
| Analysis and Computation for Finance | 15 | |
| Fractal Geometry | 15 | |
| Mathematical Theory of Option Pricing | 15 | |
| Advanced Topics in Mathematical and Computational Biology | 15 | |
| Representation Theory of Finite Groups | 15 | |
| AI and Data Science Methods for Life and Health Sciences | 15 | |
| Advanced Topics in Statistics | 15 | |
| Dynamical Systems and Chaos | 15 | |
| Fluid Dynamics of Atmospheres and Oceans | 15 | |
| Modelling the Weather and Climate | 15 | |
| Algebraic Curves | 15 | |
| Magnetic Fields and Fluid Flows | 15 | |
| Mathematics, Business and Finance Project | 30 | |
| Statistical Modelling in Space and Time | 15 | |
| Research in Mathematical Sciences | 15 | |
| Space Weather and Plasmas | 15 | |
| Bayesian Statistics, Philosophy and Practice | 15 | |
| Ergodic Theory | 15 | |
| Fundamentals of Weather and Climate Science | 15 | |
| Mid-latitude Weather Systems | 15 | |
| Climate Change Science and Solutions | 15 | |
| Topics in Analytic Number Theory | 15 | |
| Quantitative Methods and AI for Environmental Challenges | 15 | |
| Introduction to Data Science and Statistical Modelling | 15 | |
| Applications of Data Science and Statistics | 15 | |
| Data Science and Statistical Modelling in Space and Time | 15 | |
| Statistical Data Modelling | 15 | |
| Communicating Data Science | 15 | |
| Bayesian Philosophy and Methods in Data Science | 15 | |
| Optional 2 | ||
| Advanced Geotechnical Engineering | 15 | |
| Agile, Lean and Competitive Enterprise | 15 | |
| Multivariable State-Space Control | 15 | |
| Advanced CFD | 15 | |
| Structural Design | 15 | |
| Conceptual Design of Buildings | 15 | |
| Sustainable Engineering | 15 | |
| Nature-Inspired Computation | 15 | |
| Research Methodology | 15 | |
| Machine Learning | 15 | |
| Evolutionary Computation and Optimisation | 15 | |
| Computer Modelling and Simulation | 15 | |
| Computer Vision | 15 | |
| Introduction to Data Science | 15 | |
| Fundamentals of Data Science | 15 | |
| Learning from Data | 15 | |
| Social Networks and Text Analysis | 15 | |
| Stochastic Processes | 15 | |
| Machine Learning (Professional) | 15 | |
| High-Performance Computing | 15 | |
| Fundamentals of Security | 15 | |
| Building Secure and Trustworthy Systems | 15 | |
| Security Assessment and Validation | 15 | |
| Theory of Weather and Climate | 15 | |
| Number Theory | 15 | |
| Mathematical Biology and Ecology | 15 | |
| Fluid Dynamics | 15 | |
| Partial Differential Equations | 15 | |
| Applied Differential Geometry | 15 | |
| Mathematics: History and Culture | 15 | |
| Graphs, Networks and Algorithms | 15 | |
| Stochastic Processes | 15 | |
| Cryptography | 15 | |
| Statistical Inference | 15 | |
| Mathematics of Climate Change | 15 | |
| Galois Theory | 15 | |
| Computational Nonlinear Dynamics | 15 | |
| Topology and Metric Spaces | 15 | |
| Bayesian Statistics, Philosophy and Practice | 15 | |
| Integral Equations | 15 | |
| Statistical Computing | 15 | |
Please note that the module information displayed here is subject to change.
- Computer-in-the-loop control of cellular population dynamics ()
- Pattern formation via long-range cell-to-cell contact: revisiting Turing's morphogenesis hypothesis ()
- 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 ()
- The impact of hearing loss on language networks ()
- A mathematical and computational framework for neurobiological modelling: Behaviour-driven optimisation of neural connectivity ()
- What does that neuron do? A study of the neural circuits that produce swimming in the tadpole ()
- Dynamics of locomotion and phagocytosis in shape-changing cells: theory and experiments ()
- A novel opto-hydrodynamical platform for studying microorganism movement in three-dimensions ()
- Modelling convergent cell signalling pathways mediating the neurophysiological stress response ()
- Modelling the relationship between ion channel expression and electrical activity in stress-sensitive cells ()
- Linking models of large-scale brain networks with data to understand neurological disorders ()
- Personalised brain models for the management of epilepsy ()
The staff are really friendly and the lecturers are really approachable. The course is really interesting and whatever topic I have wanted to learn, we have done at Exeter.
Mathematical Biology was my favourite subject as an undergraduate, so when Covid cut my travels short, my initial plans to start working changed direction and I realised that I wanted to continue my studies. Exeter’s programme seemed exciting and innovative and I thought it would be the best fit for me. Despite the challenges provided by Covid, there were still plenty of opportunities to meet my course mates - both in person and online, and I have made great friends who share my passion and interest in this subject.
The course was seriously hard work, but thanks to that I ended up gaining so much. Before I started, I really struggled with programming and would always try to avoid it, but by the end, I felt confident in Python and MATLAB, even choosing to go on to do a technical consultancy grad scheme. As part of the MSc we were given lots of opportunities to engage with senior members of the maths department, participating in their reading groups and becoming comfortable in the world of academia/research. Our lecturers and supervisors gave us unending support throughout the course, while also allowing us to work and think more independently. I have felt myself grow both as a mathematician and as a person during my MSc.
Jess
MSc in Mathematical Modelling in Biology and Medicine
Fees
2026/27 entry
UK fees per year:
- £12,900 full-time; £6,450 part-time
International fees per year:
- £28,900 full-time; £14,450 part-time
Scholarships
The 樱花动漫 offers a wide range of scholarships to support your education, with ?7 million available for international students applying to study with us in the 2026/27 academic year, including our prestigious Exeter Excellence Scholarships. We also provide awards for sport, music and other achievements, as well as regional and partner scholarships with organisations such as Chevening, The Beacon Trust and the British Council. For more information on scholarships and other financial support, please visit our scholarships and bursaries page.
樱花动漫 Alumni Scholarship
We are pleased to offer the 樱花动漫 Alumni Scholarship, a scholarship for 樱花动漫 alumni beginning a standalone postgraduate programme in 2026/27 with us a scholarship worth 20% of the cost of your first year tuition fees.
Terms and conditions, including deadlines, apply.
Teaching and research
Data analysis, AI and mathematical modelling are crucial for developing our understanding of living systems and the mechanisms of disease. In turn, the complexity of living systems can inspire the development of new mathematical approaches.
The 樱花动漫 encourages inter-disciplinary working, and we have a growing team of researchers tackling some of the most important current problems in the field. In particular, we collaborate with experts in biology and medicine in order to use mathematics to build a better understanding of disease, thereby improving diagnosis and treatment.
Research-led teaching
We believe every student benefits from being taught by experts active in research and practice. You will discuss the very latest ideas, research discoveries and new technologies in seminars and in the field and you will become actively involved in a research project yourself. All our academic staff are active in internationally-recognised scientific research across a wide range of topics. You will also be taught by leading industry practitioners.
Assessment
Modules are either assessed by coursework only, or a mixture of coursework and an exam. For detailed information on assessment see the module descriptors in the programme structure.
Careers
Our Biomedical Data and Artificial Intelligence MSc provides students with a broad range of technical and analytical skills relevant to industrial sectors including the pharmaceutical industry, healthcare providers, software engineering and data analytics.
The skills you will acquire in data science, AI and mathematical modelling can be applied in a range of academic or industrial research fields, including epidemiology (spread of disease), neuroscience, translational medicine and synthetic biology (re-designing natural systems).
A Masters course can also lead to further academic study such as a PhD.
Dedicated careers support
You will receive support from our dedicated Career Zone team, who provide excellent career guidance at all stages of career planning. The Career Zone provides one-on-one support and is home to a wealth of business and industry contacts. Additionally, they host useful training events, workshops and lectures which are designed to further support you in developing your enterprise acumen. Please visit the Career Zone for additional information on their services.
