Research-based degrees

Postgraduate student reading a book

Leeds is a member of the Russell Group of research-intensive universities and the School of Mathematics is globally renowned for its accomplishments. In the Research Excellence Framework (REF) 2021, 98% of the research activity submitted in the Mathematics Unit of Assessment was rated as either “world-leading” or “internationally excellent”.

Our degrees are shaped by our research activity. The work our academics conduct informs the modules that we offer, allowing us to design modules that cover a wide range of topics – from stochastic financial modelling to astrophysical fluid dynamics.

All of our mathematics courses give you the opportunity to undertake a research project. The large size of our School and the diversity of the research we conduct allow us to offer a wide range of project topic choices. Our MMath, BSc courses allow you to complete an extended investigation of an advanced topic in your fourth year.

Year 4 research projects 

Throughout your course you’ll have the opportunity to study many exciting topics. Our MMath, BSc courses give you the opportunity to explore a topic that particularly interests you through an independent research project. 

You can propose a topic that you would like to base your project on or choose a topic that has been suggested by the School. Past suggested project topics include:

Applied mathematics

Temporal dynamics of species-rich ecosystems
Tidal heating of extrasolar planets    
Modelling waves in the atmosphere and ocean    
Branching processes and mathematical medicine
Self-avoiding random walks on a lattice    
Nonlinear dynamics of patterns    
The mathematics of musical tuning

Pure mathematics

Reverse mathematics
Combinatorial group theory
Complex and hypercomplex numbers
Computer-certified proofs
Surreal numbers and/or games
The size of the real line


Using random walks in exchange rate modelling
Simulating evolutionary systems 
Minority Game as an adaptive model of interacting agents in financial markets
Predicting the 3D structure of genomes using DNA contact matrices
A data analysis on the American 2000 Election     
Gaussian process emulation of complex computer models 
Statistical pattern recognition