Modelling the genomic epidemiology of antimicrobial resistant gonorrhoea

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Until recently, gonorrhoea has been a readily treatable infection. However, expanding resistance to relevant antibiotics has led to requirements for dual-therapy and raised the potential for untreatable infections. This project seeks to understand the epidemiology of gonorrhoea resistance in Australia drawing on genotypic and epidemiological data collection through two associated NHMRC grant using mathematical models that combine evolutionary and epidemiological processes. Specific aims of the project include understanding the diversity of observed gonorrhoea genotypes, the frequency of importation and to identify potential population health mechanisms for slowing geographic spread of resistant strains.

The ideal candidate would have strong mathematical and/or statistical skills combined with scientific insight and an interest in population health/biology. In terms of technical skills, in particular the candidate should meet the following criteria:

  1. At least an undergraduate qualification in a quantitative science (e.g mathematics, engineering, physics, statistics) including knowledge and understanding of differential equations and stochastic processes;
  2. Strong programming skills, particularly in high-level languages such as R or Matlab;
  3. Strong data analysis skills;
  4. Experience in computational experimentation (e.g. conducting simulation studies, comparing model-related hypotheses with data etc.);
  5. Excellent written and oral communication skills including the capacity to communicate with scientists from other disciplines such as microbiology and genetics.
Supervisory team
James
Wood

Medicine
Public Health & Community Medicine
David
Regan

Medicine
The Kirby Institute
Mark
Tanaka

Science
Biotechnology & Biomolecular Sciences
james.wood@unsw.edu.au