Postdoctoral position in predictive modelling of avian influenza spillover risk in mammalian hosts

You will be welcomed in the AnimalS health -Territories - Risks - Ecosytems (ASTRE) unit. With more than 100 permanent agents, the objective of the UMR ASTRE is to improve animal health, public health and food security in the South, particularly in the context of global changes and transitions of socio-ecosystems. International health monitoring (IHS) plays a central role in the early detection of the emergence of new pathogens or the re-emergence of existing pathogens. The post-doctoral position is integrated in the Epidemic Intelligence (EI) team of the UMR ASTRE. It is part of the European project Horizon H2025 GeoAI4EI (Leveraging Artificial Intelligence for Pandemic Preparedness and Response). This project aims to develop an open-source, reliable and ethical toolbox, based on artificial intelligence, to improve the exploitation of epidemic, epidemiological and socio-ecological intelligence data from multiple sources to strengthen preparedness and response to epidemics and pandemics in Europe. Articifical intelligence (AI) can enhance monitoring by scanning official and unofficial sources for symptom clusters signalling emerging threats. A multisource surveillance tool (MUST) was developed to collect, compile, and visualize Highly Pathogenic Avian Influenza in mammals (HPAIM) events since January 2021, combining an official source from the World Animal Health Information System (WAHIS) with two unofficial ones (EBS tools : PADI-web, ProMED-mail). Your mission will be to develop a global near-real-time Bayesian spatio-temporal model for assessing the risk of spillover of avian influenza viruses into mammalian hosts, using structured and unstructured data collected by MUST. The activities will be conducted with the EI team of ASTRE UMR in close collaboration with TETIS UMR in charge of integration of new fusion functionalities in MUST based on AI techniques to identify redundant and new information (e.g., BioELECTRA, EpidGPT23 and LLM).  You will be more specifically in charge of the following activities: Provide epidemiological inputs on MUST sources and data integration Conduct exploratory analysis to characterize geographical and temporal coverage of the different sources of data.  Developp a spatio temporal model on sporadic cases and local spread HPAIM events, and early detect anomalies Identifyi covariates (e.g. host species density, land use, seasonality) and testing potential risk factors, Provide  adapted surveillance strategy in using MUST outcomes in daily surveillance  Provide recommandations for HPAIM early detection