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Job description
The Energy and Decarbonization Directorate (DED) conducts scientific activities aimed at promoting the sustainable and secure development of decarbonized energy production and use from the subsurface, while contributing to increased energy independence. It works notably on geothermal energy and heat storage, carbon capture and storage, natural hydrogen, underground storage of energy vectors, and radioactive waste storage. This position will contribute to the R&D, public policy support, and commercial activities of the DED/I2S unit in France and internationally. The unit's main research themes include: (i) Assessment of the integrity of natural and engineered barriers (modelling, experimentation, and monitoring), (ii) Determination of the impacts of subsurface exploitation and usage (induced seismicity, pollutant migration, CO and associated impurities leakage, etc.), (iii) Evaluation of interactions and potential conflicts between subsurface uses, (iv) Monitoring of subsurface structures (sensors, passive seismics, etc.) and surface impacts (satellite interferometry, etc.), (v) Predictive modelling of coupled phenomena (reactive transport, rock-water interactions, etc.), (vi) Uncertainty quantification (Monte Carlo, meta-modelling), and (vii) Risk analysis.
The work programme is structured around the following main activities:
- Compilation, harmonization, and exploratory data analysis,
- Development of the predictive framework,
- Validation using synthetic datasets and controlled experiments,
- Regional-scale application to the Centre-Val de Loire area,
- Uncertainty assessment, interpretation, and analysis of transferability,
- Dissemination, valorization, and operational perspectives.
Overall, this project will enable both methodological advances in the field of artificial intelligence applied to geosciences and the acquisition of new regional-scale data on clay mineral distribution. This will contribute to improved assessment of shrink-swell risks and support the development of next-generation digital mapping tools.
Requirements
Candidates must hold a Master's degree or engineering diploma in geosciences, geophysics, hydrogeology, geology, computer science applied to geosciences, data science, or a related field. This project lies at the intersection of geosciences and artificial intelligence, aiming to develop innovative approaches for predictive mapping of swelling clays and clay shrink-swell susceptibility. Candidates should have strong quantitative skills and a keen interest in data analysis, modelling, statistics, and machine learning. Experience in spatial data analysis (GIS), scientific programming (Python, R, or equivalent), or artificial intelligence will be considered an asset.
The selected candidate must be motivated to work in an interdisciplinary environment combining geosciences and data science, and demonstrate strong communication and teamwork skills, Master Degree or equivalent