Developing antenatal-care (ANC)-based tools to better estimate the burden of malaria and impact of interventions.

Job description
Job summary
Funded through the Bill and Melinda Gates Foundation, this position involves working within the MRC Centre for Global Infectious Disease Analytics, at the forefront of cutting-edge inferential techniques for infectious disease analysis.

The world is likely to be dealing with aftermath of the ongoing COVID-19 pandemic well after the virus itself has been controlled, with the pandemic threatening many long-term targets towards improving global health, in particular those for the prevention of infectious diseases including Plasmodium falciparum malaria. Understanding the trajectory and future prospects for malaria control in many countries in Africa will be particularly challenging due to the suspension, in the face of the pandemic, of community-based surveys upon which estimates of malaria burden and intervention coverage are largely based. Measuring disease trends through sentinel monitoring of pregnant women attending antenatal clinics (‘ANC-based surveillance’) is a core surveillance tool for many infectious diseases and offers the prospect of substantially improved and responsive and estimates of malaria burden. However, as routine malaria testing of pregnant women within antenatal care has only begun to be adopted in recent years, tools to interpret such data in terms of population-level trends have yet to be developed.
Duties and responsibilities
The post provides an opportunity to develop novel ANC-based surveillance tools using data from antenatal clinics in Kenya, Tanzania and Zambia to substantially improve accuracy in measuring the dynamics of malaria in both spatial and temporal dimensions during a critical moment in the ongoing fight against one of the world’s highest burden infectious diseases.

Major components of the role will include fostering collaborations with global partners such as national malaria control programmes, international research institutes and the World Health Organisation and play an active role in the dissemination of results, particularly within countries in which data is being collected. You will also be expected to attend international workshops and meetings as necessary.

Essential requirements
You should have a PhD or equivalent in bioinformatics, infectious disease epidemiology, mathematical modelling, population biology, statistics or similar discipline. You should have experience of applying tailored inferential techniques to non-linear problems such as, but not limited to, Bayesian approaches, MCMC, particle filters and machine learning algorithms.

Knowledge of programming in a language appropriate for open source software (e.g. C++, Python, R or similar) is essential for this role and a knowledge of infectious disease modelling and epidemiological principles is highly valuable.

Further information
This post is full time and fixed term until 30 September 2023 and will be based at the St Mary’s Campus, Paddington. Imperial College is supportive of flexible working. The College is happy to discuss the possibility of implementing such arrangements for this post, with suitably qualified people, subject to operational requirements.

Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £36,045 - £39,183 per annum.

Type
Postdoc
Institution
Imperial College
City
London
Country
United Kingdom
Closing date
May 26th, 2021
Posted on
April 26th, 2021 16:42
Last updated
April 26th, 2021 16:42
Share