Published on May 14, 2024, by Simon Dellicour
A 2-year post-doc position is open at the Spatial Epidemiology Lab of the University of Brussels (ULB) to work on spatial models helping to target under-immunised communities during vaccination activities in the Democratic Republic of the Congo. The position should start between October 1, 2024, and January 1, 2025. The researcher will work on a project funded by Innoviris, the public organisation that funds and supports research and innovation in the Brussels-Capital Region (Belgium). This project will be performed in collaboration with Bluesquare, a global data company focused on digital health in low- and middle- income countries around the globe.
With an under-5 mortality rate of almost 8%, the Democratic Republic of the Congo (DRC) has one of the highest child death rates in the world. Among the causes of death in children, vaccine-preventable diseases are still the leading cause of death in DRC. Multiple data collection campaigns have already been carried out in DRC to better understand the spatial distribution of under-immunised children – and more are planned in the coming years. The objective of the overall project is to take benefit from these campaigns to build operational models which help target under-immunised communities during vaccination activities. Specifically, the aims are (i) to develop and validate spatial models to identify populations at risk of being under-immunised, (ii) to build on these models to develop and apply an optimisation procedure to allocate resources maximising the vaccination coverage of under-immunised populations, and (iii) to integrate modelling results into digital tools optimising resource allocation.
At the University of Brussels, the post-doctoral researcher will work within the Spatial Epidemiology Lab (SpELL, http://spell.ulb.be) and lead the analyses corresponding to the specific aims outlined above. The post-doctoral researcher will first develop a spatial model predicting local children vaccination coverage given local demographic and socio-economic variables available across the DRC territory. Various methodologies will be considered like, for instance, machine learning approaches such as boosted regression trees. Once the predictive models will be validated, the second task will consist in exploiting those models to optimise the location of future vaccination campaigns. Finally, the post-doctoral researcher will collaborate with Bluesquare’s development and data science teams to build a software application allowing key deciders in DRC to update and use the results of the predictive models in key decision-making processes such as campaign planning such as funding applications.
The candidate should hold a Ph.D. with analytical skills in spatial modelling/epidemiology, should have a strong interest in epidemiology, and should have demonstrated computational, communication and writing skills (English). Knowledge and use of the programming language R is required.
Applications should include a cover letter, a curriculum vitae, PDFs of the three most representative publications, and a list of three references with e-mail contact information. Applications should be submitted as soon as possible.
Dr Simon Dellicour (simon.dellicour@ulb.be)