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MSc Mathematical Modelling (Biology and Medicine)

University of Exeter


  • Develop skills in fundamental aspects of mathematical biology
  • Learn about mathematical modelling and dynamical systems theory applied to biology, ecology, neuroscience, synthetic biology and medicine, as well as tools for advanced data analysis.
  • 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.


This degree can lead to research roles in many sectors including working for charities, hospitals and healthcare providers. The skills you will acquire in mathematical modelling can be equally well applied to other fields of study such as understanding climate change or conservation and ecology.

For many students a masters course can also lead to further academic study such as a PhD.

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  • Advanced Mathematics Project
  • Engaging with Research
  • Computational Modelling
  • Mathematical Biology and Ecology
  • Advanced Topics in Mathematical Biology
  • Mathematical Modelling in Biology and Medicine
  • Advanced Topics in Statistics
  • Dynamical Systems and Chaos
  • Statistical Modelling in Space and Time
  • Applications of Data Science and Statistics
  • Computational Nonlinear Dynamics
  • Partial Differential Equations
  • Nonlinear Systems and Control
  • Stochastic Processes
  • Statistical Inference: Theory and Practice
  • Special Topics in Statistics
  • Requirements

    Listed below are the documents required to apply for this course.
    1 year


    Sep 2024

    Start Month

    Aug 2024

    Application Deadline

    Upcoming Intakes

    • September 2024

    Mode of Study

    • Full Time