Self-funded PhD applications are welcome.
Computational investigation of microbial communities involved in methane production (2015-16)
The overall goal is to better understand microbial fermentation technology with a view to developing a sustainable approach for producing energy and other valuable products from waste biomass. The project will use mathematical modelling and computational approaches to investigate the complex interactions that occur in complex microbial communities, especially metabolite cross-feeding. The long term goal is to optimise the breakdown of variable or defined feedstocks in anaerobic digestion (AD) systems and to be able to manipulate the yield of particular fermentation end products (eg. alcohols, acids, gases).
Applicants should have a good first degree in a relevant physical/mathematical science, some experience in computer programming and an interest in the application of mathematical approaches to biological systems.
Bioinformatic analysis of bacterial genome evolution (2015-16)
Bacterial genomes are relatively small in size but very varied in content and composition. Public databases provide a huge and growing resource of bacterial genome data that has barely been mined to date, and we also have access to our own new data that require analysis before publication. This opens up numerous possibilities for projects that use or develop bioinformatic tools for sequence analysis. One possibility would be to seek to identify the highways for bacterial gene traffic by tracking the distribution of genes that have spread across many bacterial groups. By comparing sequences, the pathways of transfer can be reconstructed, and evidence for selection may be detected. A different project might explore the functional classes of genes in different locations in the genome – the core genome, genomic islands, plasmids, etc. – in order to understand how bacterial genomes are constructed and maintained in the face of constant rearrangement and environmental challenges. Such projects require familiarity with computer programming and analysis languages such as Python and R, so a Masters degree in bioinformatics, or similar relevant experience, is normally a prerequisite.