Developing an individual-based mathematical model for antibiotic resistant bacteria in urinary tract infections

Antimicrobial resistance is an increasingly serious threat to global public health. New resistance mechanisms are emerging and spreading globally, threatening our ability to treat common infectious diseases, resulting in prolonged illness, disability, and death.

Multidisciplinary research into antimicrobial resistant infections will allow the knowledge and expertise of several important fields to be amalgamated, with a greater chance of progress in addressing this problem. Mathematical models play an essential part in this endeavor.

We are seeking a PhD student to work with Dr Ruth Bowness within the Infection and Global Health Divison in the School of Medicine and the Mathematical Biology group in the School of Mathematics and Statistics on a project at the interface of mathematics and medicine. The student will also work closely with Professor Mark Chaplain and Dr Tommaso Lorenzi from the School of Mathematics and Statistics and the Gillespie group from the School of Medicine.

The project involves creating an individual-based mathematical model to study Enterobacteriaceae in urinary tract infections (UTIs). This project will focus on carbapenemase-producing Enterobacteriaceae (CPE), which can lead to Enterobacteriaciae becoming resistant to carbapenems, the usual antibiotic treatment of Enterobacteriaceae in UTIs. CPE have been steadily spreading worldwide in the last decade. Antibiotic treatment options for these multidrug-resistant infections are limited and clinicians are unclear as to the most effective antibiotic regimens. The mathematical model will be capable of simulating new treatment strategies, comparing the efficacy of various regimens.

Applications

Applicants must be a UK national or have permanent leave to remain in the UK. Applicants should have a good first degree in mathematics, computer science or another scientific discipline with a substantial numerical component. Candidates must be willing to learn advanced computational modelling techniques and be interested in interdisciplinary systems biology research. A masters-level degree is an advantage.

Applications are in the form of a C.V. and cover letter, describing your interest in the project and your suitability. Applications or informal enquiries may be made directly to the primary supervisor.

Closing date for applications: 27 April 2018
Interviews: Early May 2018
Anticipated start date: 27 September 2018

Contact

Dr Ruth Bowness
rec9@st-andrews.ac.uk