Post-doc in artificial intelligence / spatial epidemiology

Description Institution: IHU Sepsis is a hospital–university research institute dedicated to advancing the understanding of sepsis and developing innovative strategies for prevention. The institute brings together experts in medicine, epidemiology, data science, and biology, with a strong focus on translational public health impact. Project Overview Within the framework of a national research project, the postdoctoral researcher will investigate spatial variations in sepsis incidence across France using large-scale public ecological datasets (e.g. INSEE, ATMO, DREES, Santé Publique France). The project combines advanced spatial analysis and state-of-the-art artificial intelligence methods to identify territorial risk patterns and underlying ecological determinants. Key Responsibilities Manage large territorial ecological databases (social, environmental, and health data). Perform classical and advanced spatial analyses to identify high-risk areas. Develop predictive and explanatory models using: Machine learning Bayesian spatial and spatio-temporal models Deep learning and spatio-temporal AI Graph-based models Produce high-quality maps, visualizations, and interactive dashboards. Publish results in peer-reviewed journals and present at international conferences. Candidate Profile PhD in spatial epidemiology, data science for health, computer science, or a related field. Strong expertise in deep learning, spatial and spatio-temporal modeling and AI applied to public health or geospatial data. Proficiency in Python and GIS tools (QGIS, ArcGIS). Ability to work independently in a multidisciplinary research environment. Excellent written and oral communication skills in English (French is an asset but not required). Duration: 24-month postdoctoral contract, full-time. Location: UVSQ, Paris-Saclay How to apply: If interested, please send your CV in a motivational email to zaineb.garcia@univ-lille.fr and laetitia.huiart@uvsq.fr