Research Associate in Geospatial Modelling

Location/campus: White City Campus - Hybrid

About the role

We are aiming to develop novel geospatial modelling approaches to analyse trends in the genetics of malaria transmitting mosquito populations in Sub-Saharan Africa. Our results will inform key policy decisions regarding the optimal deployment of critical malaria control interventions, such as new types of insecticide-treated bednets. You will work within an international team to inform strategic malaria control in collaboration with world-leading research teams in the UK and Cameroon, with links to the WHO.

We are aiming to develop novel geospatial modelling approaches to analyse trends in the genetics of malaria transmitting mosquito populations in Sub-Saharan Africa. Our results will inform key policy decisions regarding the optimal deployment of critical malaria control interventions, such as new types of insecticide-treated bednets. You will work within an international team to inform strategic malaria control in collaboration with world-leading research teams in the UK and Cameroon, with links to the WHO.

What you would be doing

Working with cutting-edge methodologies in geostatistics and machine learning, you will analyse a rich data set recording the frequencies of genetic mutations that confer insecticide resistance in wild mosquito samples collected throughout malaria-endemic countries in Sub-Saharan Africa. You will apply open-source models of malaria transmission dynamics developed by our teams (https://github.com/mrc-ide/malariasimulation) to link geospatial predictions of insecticide resistance to malaria disease incidence. Resulting models and maps will identify areas where targeted deployment of novel insecticidal interventions will have maximal malaria control benefit. You will work within an established world-leading team with decades of experience in the mathematical modelling of malaria to inform policy.

What we are looking for

We are seeking a Research Associate with the following characteristics:

Essential:

• PhD or equivalent in statistics, biostatistics, applied mathematics, computational biology, epidemiological modelling, or a related methodological discipline.
• Interests in infectious disease ecology and global public health management.

Desirable:

• Experience in the implementation of mathematical or statistical models and model fitting, including Bayesian model fitting.
• Experience of management and analysis of large multidimensional real world data sets.

What we can offer you

• The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
• Opportunities to build your international profile including travel for conferences and workshops.
• Grow your career: gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
• Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).
• Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

Further information

Our team is part of the malaria modelling group at the Department of Infectious Disease Epidemiology (Malaria Modelling | Faculty of Medicine | Imperial College London).

This role is offered on a full-time, fixed-term basis for one year in the first instance.

If you require any further details about the role, please contact:

Dr Penelope Hancock – p.hancock@imperial.ac.uk.

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