We welcome enquiries from students interested in studying for a PhD in mathematical biology. Below we list some sample projects that we could currently offer.
UK and EU students may be eligible for funding, see here for details. Formal applications must be made through the University of Sheffield's online application form, available here. We strongly encourage you to contact the potential supervisor for informal enquiries before making a formal application.
Example PhD projects on offer for 2025
Modelling disease dynamics in forests in changing environments (Supervisor: Alex Best)
The evolution of hosts and their parasites in spatially-structured populations (Supervisor: Alex Best)
Multiscale modelling of tissue patterning and morphogenesis (Supervisor: Alexander Fletcher)
Quantitative modelling and analysis of stem cell dynamics in health and disease (Supervisor: Alexander Fletcher)
Inferring cell biological processes through data-efficient multi-fidelity modelling (Supervisor: Alexander Fletcher)
Developing sustainable software for mathematical biology (Supervisor: Alexander Fletcher)
Investigating a polarity switch in bird wing feather development (Supervisor: Alexander Fletcher)
The effect of autocorrelation in animal movement on emergent space use patterns (Supervisor: Jonathan Potts)
Non-local PDEs for understanding the spatial distributions of populations in ecosystems (Supervisor: Jonathan Potts)
Undergraduate students at the School of Mathematical and Physical Sciences interested in mathematical biology may want to consider the following courses:
This Level 2 course demonstrates, in a series of case studies, the use of applied mathematics, probability and statistics in solving a variety of real-world problems. The module includes a case study on mathematical modelling drug dosages and pharmaco-kinetics, a topic in mathematical physiology.
To find out more contact the course lecturer for this case study, Prof. Alexander Fletcher (a.g.fletcher@sheffield.ac.uk).
This Level 3/4 course provides an introduction to the mathematical modelling of the dynamics of biological populations. The emphasis is on deterministic models based on systems of differential equations that encode population birth and death rates. Examples are drawn from a range of different dynamic biological populations, from the species level down to the dynamics of molecular populations within cells.
To find out more contact the course lecturer, Prof. Jonathan Potts (j.potts@sheffield.ac.uk).
Mathematical modelling enables insight in to a wide range of scientific problems. This Level 3/4 module provides a practical introduction to techniques for modelling natural systems. Students learn how to construct, analyse and interpret mathematical models, using a combination of differential equations, scientific computing and mathematical reasoning. Students learn the art of mathematical modelling: translating a scientific problem into a mathematical model, identifying and using appropriate mathematical tools to analyse the model, and finally relating the significance of the mathematical results back to the original problem. The module includes at least one case study in the area of mathematical biology.
To find out more contact the course lecturer for this case study, Dr Alex Best (a.best@shef.ac.uk).
Level 4 mathematics and statistics students have the opportunity to undertake a research project supervised by a member of staff. Project titles in mathematical biology are available each year for MAS6041 (MMath) and we welcome enquiries from any students interested in undertaking a project with us. We encourage anyone interested to read our research interests and make contact with the relevant member of staff. Projects within mathematical biology that have been recently offered include:
Infectious disease dynamics with local interactions
Measles: a case study of seasonally-forced disease dynamics
Modelling biological invasions
Modelling cell fate specification in early embryonic development
Modelling marine ecosystems
Symmetry-breaking and pattern formation in biological tissues
The mathematics behind animal territory formation