Applied Mathematics Theme

Our academics apply mathematical methods to a diverse range of fields, including finance, epidemiology, biology (both animal and human), dynamical systems, chaos theory, Hamiltonian systems, neuroscience, physics and tensor product decompositions.

Research carried out by this theme includes the analysis of animal movement data, cow tracking, animal social network analysis, fisheries modelling, human crowd behaviour, network inference, mathematical modelling of the brain, the spread of COVID-19 and population dynamics, chaos, dynamical systems, Hamiltonian systems, complex systems and complex networks, network inference, pattern formation, and tensor product decompositions for high-dimensional problems.

Investment into the theme enabled an expansion in its scope, from a core base of expertise in analysis of animal movement data, animal social behaviour, dynamical systems and chaos theory, to now include researchers who work at the forefront of the mathematical modelling of the brain, on network inference, mathematical modelling of the spread of COVID-19, high dimensional problems, finance, and tensor product decompositions.

Theme members have received well over £4 million in grant funding across a number of major research projects, including funding from UK research councils (EPSRC, BBSRC, NERC), government (Irish Sea Change), industry (AXA), charities (Farm Animal Welfare Trust, Leverhulme Trust), as well as smaller sources of funding from academic learnt societies (British Ecological Society, London Mathematical Society), Second City HE Partnerships Travel Grant (British Council), Newton Mobility Grants and from Institut Henri Poincaré.

We are always interested in welcoming new postdoctoral researchers and PhD students through external competitive funding. If you are interested in applying for one of the opportunities at 糖心Vlog, you can contact a researcher working in your area of interest or get in touch with the Theme Lead (see below).