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Computational and Polymer Sciences to Engineer Microbial Physiology


Project Description

Mathematical modelling and statistical inference are key tools in understanding the life sciences. In this project, we will develop differential equation models and apply statistical inference techniques to understand how polymers can be engineered to be of practical use in microbiology. In particular, recently there has been an increase in the use of polymers to interface with bacteria and other microorganisms, either to treat microbial infections, to prevent and control biofilm formation, or as a platform to grow and maintain microbial cultures for biotechnology. However, what is often overlooked in these applications is how bacteria adapt to the presence of these polymeric materials and how, more often than not, unwanted responses such as increased virulence are activated in the presence of these polymers.
We will develop the computational methodology to correlate how relevant polymer properties (e.g. charge, hydrophobicity) affect critical microbial phenotypes (biofilms, virulence). Importantly, we will develop predictive mathematical models to guide the design of polymers that should induce specific behaviours in a given microbe.
We are looking for a highly motivated PhD candidate willing to work at the interface between mathematics, computational analysis and chemistry. Ideally, the candidate should have a degree in mathematics, or a related discipline.
This project is highly multidisciplinary and involves a collaboration between Dr Sara Jabbari (School of Mathematics) and Dr Francisco Fernandez-Trillo (School of Chemistry). The PhD candidate will work alongside another PhD student working in the development of polymers. Both PhD candidates will be trained in microbiology and join a vibrant research team of applied mathematicians, chemists, pharmacists, biochemists and microbiologists.
For further details about the project, please contact Dr Sara Jabbari () or Dr Fernandez-Trillo ().

Funding Notes

This Project is funded by the Leverhulme Trust. Leverhulme Doctoral Scholars will receive maintenance costs at Research Council rates and tuition fees at the rate for UK/EU students. In 2019/2020 the maintenance grant for full-time students was £15,002.99 per annum. International applicants who can pay the difference between the Home and International Fees would also be welcome to apply.
Please contact for details regarding funding and the application procedure.

References

1) Predictive modelling of a novel anti-adhesion therapy to combat bacterial colonisation
of burn wounds. Roberts et al. PLOS Comp. Biol. (2019) e1007211.
2) Mathematical modelling of the antibiotic-induced morphological transition of P. aeruginosa. Spalding et al. PLOS Comp. Biol. (2018) e1006012.
3) Bacterial fitness shapes the population dynamics of antibiotic-resistant and -susceptible bacteria in a model of combined antibiotic and anti-virulence treatment. Ternent et al. J. Theor. Biol. (2015) 372: 1-11.
4) Mathematical modelling reveals properties of TcdC required for it to be a negative regulator of toxin production in C. difficile. Jabbari, Cartman, King. J. Math. Biol. (2015) 70: 773-804.
5) Computational modelling of occludin trafficking, demonstrating continuous endocytosis, degradation, recycling and biosynthetic secretory trafficking. Fletcher et al. PLOS ONE (2014) 9:e111176.

How good is research at University of Birmingham in Mathematical Sciences?

FTE Category A staff submitted: 40.00

Research output data provided by the Research Excellence Framework (REF)

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