Advanced matrix-analytic methods with applications. Over the last twenty-five years, matrix-analytic methods have proved to be very successful in formulating and analysing certain classes of stochastic models. Motivated by applications, this project will investigate more advanced matrix-analytic methods than have hitherto been studied.
Creating new stochastic models to understand the evolution of gene families. This project aims to extend stochastic modelling techniques in order to develop mathematically rigorous and biologically relevant models for the evolution of gene families. The project expects to model evolutionary processes such as gene retention, duplication and loss, and the generation of new gene functions. The duplication and subsequent re-purposing of genes is thought to be a key mechanism for generating evolution ....Creating new stochastic models to understand the evolution of gene families. This project aims to extend stochastic modelling techniques in order to develop mathematically rigorous and biologically relevant models for the evolution of gene families. The project expects to model evolutionary processes such as gene retention, duplication and loss, and the generation of new gene functions. The duplication and subsequent re-purposing of genes is thought to be a key mechanism for generating evolutionary novelty. By applying these models to genome data, the project expects to be able to quantify the importance of these different evolutionary mechanisms. The project will strengthen collaborative links between researchers in stochastic modelling and molecular evolutionary biology.Read moreRead less
Modeling Healthcare Systems. An efficient healthcare system is essential for the well-being of any society. The aim of the project is to develop major advances in the mathematical modelling of healthcare systems, in order to improve efficiency, and ultimately, patient health. The first expected outcome is the development of mathematical models that constitute a high-level description of patient flow through hospitals and subacute care, so that demands for emergency and elective capacity are met ....Modeling Healthcare Systems. An efficient healthcare system is essential for the well-being of any society. The aim of the project is to develop major advances in the mathematical modelling of healthcare systems, in order to improve efficiency, and ultimately, patient health. The first expected outcome is the development of mathematical models that constitute a high-level description of patient flow through hospitals and subacute care, so that demands for emergency and elective capacity are met given limited resources. The second is the development of a bed allocation algorithm that allocates patients to appropriate wards, so as to optimise the set of performance indicators of the system under appropriate constraints, given the current ward occupancy.Read moreRead less