Complex mathematical models are increasingly being used for research and decision making in academia, health and industry. However, the robust calibration and analysis of computationally intensive models is infeasible using currently accessible technologies, which can lead to over-confident or wrong information being given to decision makers. The successful candidate will join an exciting project to develop a history matching and model emulation package in R, that will allow infectious disease modellers to routinely and comprehensively calibrate complex mathematical models.

The successful applicant will work in close collaboration with a programmer/statistician, and with mathematical modellers. They will be responsible for leading the testing of the developing software package, writing software documentation and tutorials, and working with a number of different modelling groups to improve the usability of the software. The post-holder will be supervised by Prof Richard White and will join a highly successful and supportive TB modelling group.

The post-holder will require a postgraduate degree in in a quantitative discipline such as epidemiology, control of infectious diseases, mathematics, or computational biology, or similar research experience, as well as proficient knowledge of R or other programming language and excellent interpersonal skills. Further particulars are included in the job description.