Job description

Job summary

We are looking for a Research Fellow in mathematical modelling of sexually-transmitted infections to join our group. The post is a great opportunity to develop a broad range of skills and experience, and build an international network of collaborators. Our research focuses on understanding the natural history, epidemiology, and transmission patterns of STIs and the effectiveness and cost-effectiveness of control measures, including combating drug resistance and combines infectious disease modelling with studies of patient and population behaviour, health services research, and health economics.

It is an exciting time to be addressing the burden of STIs, with gonorrhoea vaccine trials underway, new vaccines in development for several STIs, new antibiotics becoming available, new diagnostics (including rapid tests that detect drug resistance), and new studies of sexual behaviour patterns and infection natural history, as well as improvements to surveillance systems. It is important to work out how best to use new technology, with 1 million new infections acquired per day globally, and diagnoses increasing in many countries. A common challenge with sexually-transmitted infections is that risk of acquisition and transmission of infection are often concentrated in particular risk groups – which can be different for each infection.

Duties and responsibilities

The range of activity in the group, described in the section above, makes it possible to tailor the role to your skills and interests, so you will perform a combination of some of the following:

• analysing data from research studies and surveillance to improve understanding of the natural history of monkeypox, gonorrhoeae, M. genitalium and/or C. trachomatis;


• analysing surveillance data to understand trends over time and understand local-level inequalities to improve targeting of interventions;


• developing model code to perform Bayesian evidence synthesis of multiple data sources to provide insights in to epidemiology of the infections that we are working on (e.g. there are now several years of surveillance data available for genitalium, making it possible to update our previous modelling work);


• developing code to model the impact of interventions including vaccination and use of novel diagnostics;


• genetic sequence analysis of gonorrhoeae to improve understanding of its natural history and transmission.

Essential requirements

• A PhD with relevant data-analysis and coding skills


• Extensive knowledge of infectious disease epidemiology / modelling


• Strong skills in coding in R, Python, or C/C++


• A record of high-quality publications in respected peer-reviewed journals

Ideally, you will have some of the following skills and knowledge but they are not essential as training will be provided:

• Strong skills in statistical analysis (ideally in R)


• Knowledge of Bayesian methods


• Knowledge of STI epidemiology


• Experience of cost-effectiveness analysis

Further information

The post is full time fixed term until 31 March 2025, based initially at the St Mary’s Campus.

From Autumn 2023, the School of Public Health will be relocating to the White City campus.

For further information you are welcome to contact Professor Peter White (p.white@imperial.ac.uk).

The College is currently trialling a Work Location Framework until early 2023.  Hybrid working may be considered for this role and the role holder may be expected to work 60% or more of their time onsite, with 40% the minimum time spent onsite.  The opportunity for hybrid working will be discussed at interview.

Documents

• Research Fellow in Modelling STIs.pdf