General comments

I am interested in recruiting students on two main strands of computational and mathematical research -- modelling problems in microbiology and modelling collective behaviour. Please do contact me if you are interested in related projects in this general field.

I am also interested in potential collaborations in these areas. The University of York encourages and provides support for any potential fellowship applications.

Ph.D. Projects

The tight coupling between the instantaneous growth phase of bacteria, the performance of the various gene regulatory networks and the local environment is a complex problem for which there exists only limited current computational work. By taking advantage of modern trends in computing, in particular the use of massively parallel GPGPU devices, we aim to develop a coding environment that couples these three differing regimes together. By using techniques more usually used in ecology, we will derive statistical measures for spatial position from experimental data from the van der Woude lab. The ultimate goal of the project is to understand correlations between gene expression and spatial position and how this may impact on function of the bacterial collective.

This project will require a strong computational background and a keen interest in modelling prokaryotes. The student should be well versed with a compiled programming language, previous knowledge of parallel architectures will be an advantage but not essential.

In prokaryotes, a respiratory chain is necessary which to pass electrons from their initial production from the oxidation of NADH through to their eventual usage at the terminus of the chain to reduce Oxygen (aerobic) or a differing substrate, typically Nitrogen (anaerobic). The design and complexity of this chain varies significantly between organisms adapted to living in different environments and the aim of this project is to investigate the function and working of these varied respiratory systems. The primary model of interest is the asymmetric exclusion process (ASEP) which we will use as the basis for the modelling of the chain.

The project will require strong analytical skills as well as computational modelling; it represents an opportunity for a student with a background in Mathematical Physics to investigate applications to the life-sciences interface as well as work in an interdisciplinary team. This project also supports the work of experimental projects funded through the White Rose network MICROSYS.

Phase variation is the mechanism by which bacteria are able to express multiple, distinct phenotypes with the same genotype. This process has significant consequences for the resistance of bacteria to various human interventions; a phenomenon often termed persistence. This project has multiple threads depending upon the skills and interests of the student. Possibilities include: 1) detailed stochastic simulation of a case study system (ag43 switch in E.coli) 2) examination of the role of gene-transfer in the phase varying system within a spatial structured population 3) extension of existing analytical work on the optimal conditions for stochastic switching.

This is strongly mathematical project, but some experience of computational would be required. The candidate should demonstrate an interest in problems in mathematical biology and immunology

One application of systems biology is the whole genome reconstruction of metabolic networks from bacteria which are then analysed using constraint-based modelling, also known as flux balance analysis (FBA). The method is useful as it allows testable hypotheses about the properties of the metabolic network of the bacterium based on the stiochiometires of the reactions that it contains and does not require kinetic data about rates of enzymatic or transporter reactions. However, often these data are available and in this project the student will investigate a number of computational approaches to using kinetic data within a constraint-based modelling framework.

This project is computational in nature, and programming skills would be essential. Aptitude in any of microbiology, biochemistry, systems biology or mathematics would be advantageous.

Building on recent work, this Ph.D. will look at the evolution of aggregation strategies in response to predation. Using tested techniques and new algorithms this project will simulate the motion of collective shoals and flocks and allow their properties to evolve at an individual level. We are interested in the evolution of higher level avoidance strategies and manoeuvres that characterise these large macro-scale groupings.

This project is computational in nature, and programming skill would be essential. Aptitude in theoretical ecology or mathematics would be advantageous. There is an additional opportunity within this project for a student of a more engineering focus to transfer the coding environment to the player/stage platform and instantiate the simulations onto a physical system (in conjunction with the Timmis Lab).

The goal of this Ph.D. is to understand the roles and priorities of foraging within a group and the extent to which group foraging promotes or penalises the fitness of its constituent members. Whilst it is widely accepted that predator avoidance behaviour is a primary evolutionary cause the motivates group living, there exist empirical observations and simulation models that have investigated the impact of foraging in differing environments on group behaviour.

To seek optimality in these individual based models the work will involve implementing genetic algorithms utilising non-standard applications that better reflect the population dynamics and life histories of the individual agents. For example, foraging in many marine species is a seasonal event, distinct from mating and reproduction. This theme of research has many practical applications, including group foraging efficiency, collision risk analysis (with links to an independently funded FERA project evaluating wind farm design and placement with respect to known trajectories of flocks of birds) and climate change impact on large scale migratory events (linking to NERC/CEFAS-funded project on management of migratory fish stocks)

The student should be an experienced programmer with a lively interest in the application of computational and mathematical techniques to environmental applications. A strong background in mathematics would be distinct advantage.