Snabbfakta
-
- London
Ansök senast: 2024-12-07
Research Assistant in Spatial Epidemiology
Join our research team as an AI Researcher in Spatial Epidemiology, funded by the Schmidt Sciences AI2050 grant, to apply advanced AI techniques, such as deep generative modelling, probabilistic programming and, potentially, geometric learning, to tackling critical challenges in spatial epidemiology. Contribute to innovative projects in disease mapping, spatial statistics, and population genetics while disseminating ground-breaking findings to both academic and policy-making audiences
In this role you will leverage advanced AI techniques, such as deep generative modeling, to develop cutting-edge models in computational epidemiology, focusing on areas including but not limited to spatial statistics, population genetics and broader disease surveillance.
You will adopt existing and develop new computational statistical, machine learning and deep learning methods for analyzing spatiotemporal health data. Your work will include creating and disseminating replicable and reproducible computational workflows, as well as training practitioners in these new methods.
Additionally, you will communicate your research findings effectively to academic audiences through conferences and journal publications, and to policymakers through national and international meetings. You will be responsible for submitting your research publications to peer-reviewed journals and actively seeking external research funding.
Collaboration is a key aspect of this role. You will work closely with various departments within the SPH (EBS + DIDE) and have the opportunity to interact with researchers from prestigious institutions such as Oxford, Copenhagen, Singapore, Switzerland, and South Africa whenever there is a suitable fit.
Relevant literature:
This position comes with
