| UCAS code | 1234 |
|---|---|
| Duration | 1 year full time |
| Entry year | 2025 |
| Campus | Streatham Campus |
| Discipline | Mathematics |
| Contact |
| Typical offer | A 2:1 degree or equivalent |
|---|---|
Overview
- 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
Fast Track (current Exeter students)
Professor Krasimira Tsaneva Atanasova talks about Biomedical Data and Artificial Intelligence at the University of Exeter. (This video refers to the mathematical modelling component of the course.)
Top 20 in the UK for Mathematics
18th in the Complete University Guide 2025
Top 50 in the world for our Mathematics and Computer Science research
CWTS Leiden Ranking 2023, by percent of articles in the top 10% most-cited
Wide range of exciting and high-impact research projects
Research expertise in climate modelling and statistics; control and dynamics; systems biology; astrophysical fluid flows and number theory
Top 20 in the UK for Mathematics
18th in the Complete University Guide 2025
Top 50 in the world for our Mathematics and Computer Science research
CWTS Leiden Ranking 2023, by percent of articles in the top 10% most-cited
Wide range of exciting and high-impact research projects
Research expertise in climate modelling and statistics; control and dynamics; systems biology; astrophysical fluid flows and number theory
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.
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 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.
Course content
The modules we outline here 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.
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| MTHM021 | Advanced Mathematics Project | 60 |
| MTHM007 | Engaging with Research | 15 |
| MTH3006 | Mathematical Biology and Ecology | 15 |
| MTHM009 | Advanced Topics in Mathematical Biology | 15 |
| NSCM005 | Mathematical Modelling in Biology and Medicine | 15 |
| MTHM015 | AI and Data Science Methods for Life and Health Sciences | 15 |
Optional modules
| Code | Module | Credits |
|---|---|---|
| Select 15 - 45 credits: | ||
| MTHM017 | Advanced Topics in Statistics | 15 |
| MTHM018 | Dynamical Systems and Chaos | 15 |
| MTHM033 | Statistical Modelling in Space and Time | 15 |
| MTHM503 | Applications of Data Science and Statistics | 15 |
| MTHM**** | Maths Level 7 module | 15 |
| Select 0 - 15 credits | ||
| MTH3039 | Computational Nonlinear Dynamics | 15 |
| MTH3008 | Partial Differential Equations | 15 |
| MTH3011 | Nonlinear Systems and Control | 15 |
| MTH3024 | Stochastic Processes | 15 |
| MTH3028 | Statistical Inference: Theory and Practice | 15 |
| MTH3027 | Special Topics in Statistics | 15 |
| MTH3049 | An Introduction to Causal Inference | 15 |
| ECMM**** | ECMM Level 7 module | 15 |
- 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)
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
2025/26 entry
UK fees per year:
- £12,600 full-time; £6,300 part-time
International fees per year:
- £28,600 full-time; £14,300 part-time
Fee information
Fees can normally be paid by two termly instalments and may be paid online. You will also be required to pay a tuition fee deposit to secure your offer of a place, unless you qualify for exemption. For further information about paying fees see our Student Fees pages.
UK government postgraduate loan scheme
Postgraduate loans are now available for Masters degrees. Find out more about eligibility and how to apply.
Scholarships
We invest heavily in scholarships for talented prospective Masters students. This includes over £5 million in scholarships for international students, such as our Global Excellence Scholarships*.
For more information on scholarships, please visit our scholarships and bursaries page.
*Selected programmes only. Please see the Terms and Conditions for each scheme for further details.
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 University of Exeter 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. The project entails a short initial report or project proposal of around 1,000 words, a public presentation and a dissertation of 10,000 to 20,000 words. This is assessed by your supervisor and a second marker.
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.
