PhD Researcher in Earth and Environmental Sciences – Machine Learning for Water Resource Management

This PhD position is part of the Horizon Europe INTEGRATOR project, a collaborative effort across 11 European countries. The successful candidate will work at the Institut Terre Environnement Strasbourg (ITES) to create high-resolution indicators from satellite and in-situ data, integrating machine learning and text mining to assess biophysical, hydrological, and socio-environmental dynamics. The research will inform early warning systems and adaptive water governance in the face of climate change. The PhD will leverage Copernicus services and multi-sensor satellite data (e.g., Sentinel-1/2/3, SMOS) to monitor vegetation, soil moisture, and water levels, while NLP techniques will analyze regulatory and media sources for socio-environmental pressures. The candidate will collaborate with European partners and contribute to a Digital Water Intelligence System (DWIS).

• Develop machine learning models to process high-resolution Earth observation data (e.g., Sentinel-1/2/3, SMOS) for hydrological and biophysical indicators.
• Integrate satellite imagery, in-situ measurements, and NLP-extracted socio-environmental data to assess water resource resilience.
• Collaborate with European partners to implement a Digital Water Intelligence System (DWIS) for early warning and adaptive management.
• Publish findings in peer-reviewed journals and present results at international conferences.
• Contribute to project deliverables, including technical reports and policy-relevant insights for water governance.
• Participate in project meetings, workshops, and summer schools organized by the INTEGRATOR consortium.