Research in Mathematical Sciences is undertaken by the Mathematics Research Group, formed from staff from the Department of Physical, Mathematical & Engineering Sciences and other associated staff from the Faculty of Science and Engineering at the University of Chester.
The research of the Group is organised within the following overlapping themes:
- Algebra, Number Theory and applications of Group Algebras to Coding Theory.
- Analysis, Applied Analysis and Numerical Analysis.
- Mathematical Modelling.
- Stochastic Analysis.
The University’s targeted research funding has been bolstered by external funders including: UKRI, EPSRC, the London Mathematical Society and industry.
7 staff were identified as having significant responsibility for research in REF2021, leading to a requirement for 16 outputs to be submitted.
Research outputs submitted to REF2021 are included in the Mathematics Collection of ChesterRep, the University of Chester’s online research repository.
The impact of research in this unit was exemplified through the following case studies:
Mathematical modelling leads to advances in immunology and drug development: Research involving mathematical modelling is helping to unravel the complexities of key areas of biomedicine. This study of the mammalian immune system focuses on two areas: (1) genetic evolution of HIV within the host during infection, and (2) dendritic-cell-based immunotherapy. The research has influenced understanding by biomedical practitioners of control parameters, the immune response and viral resistance to drugs. The Unit’s consequent involvement in developing the COMPIT tool has enabled mathematical modelling to play a key part in 3Rs (Replacement, Reduction and Refinement) of animal experimentation in the development of new drugs as well as reducing the cost and the time taken to bring a new drug to market.
Expert Advice to Major Funding Agencies Internationally: This impact case study concerns the impact of Neville Ford as an expert providing advice to a range of international funding agencies. This has enabled the funders to enhance the effectiveness of funding decisions and to promote maximum impact to meet their objectives to support excellent science and its impact in health, engineering, the environment, the economy, and in the development of future excellent scientists.