Mathematical biology and medicine

Mathematical immunology: we develop modelling of how the immune system works, and how it reacts against different viral and bacterial pathogens.
Mathematical epidemiology: we are interested in developing new analytical and numerical tools for understanding how pathogens spread among individuals in a given population. The interest here is in assessing how different factors (such as population heterogeneities, or spatial considerations) can affect the infection spread, and to analyse the efficacy of potential infection control strategies.

Statistical bioinformatics: our work covers the statistical methodologies for the analysis of genomic, genetics, and protein structure.
Genomics: our research focuses on how to estimate genomic information from next-generation sequence data and how that information can be utilised for prediction of cancer patients’ clinical outcome. In genetics, statistical methodologies are developed to deal with rare variant association test and fine mapping. In protein structure analysis, the focus is in the protein structure prediction, clustering, and classification.

We are interested in developing mathematical and computational tools to understand the mechanisms allowing the maintenance of coexistence in many-body systems, fixation of specific traits and emergence of complex patterns, from bacteria up to large-scale patterns in ecological systems, from molecular level to collective human and animal behavior. Several fields of Mathematics and Physics provide rigorous methods and powerful tools which can be fruitfully applied to understand such challenging problems. These include stochastic processes, non-equilibrium statistical mechanics, evolutionary game theory, finite-size scaling, Bayesian methods, machine-learning and agent-based models.

We have opportunities for prospective postgraduate researchers. Find out more.

If you are interested in collaborating with us or joining our research team, please get in touch with a relevent member of our group.