We are pleased to announce the opening of a postdoctoral position at the Center for Applied Mathematics (CMA) and the Geosciences Center of Mines Paris – PSL, as part of the Clim’Seine project funded by the Transition Institute 1.5.
This position focuses on developing artificial intelligence methods (deep learning) for the monitoring, analysis, and prediction of groundwater and surface water temperature, in the context of climate change and sustainable water and energy resource management. We are seeking an early-career researcher with expertise in machine learning, statistics, or data visualization.
Position details:
- Duration: 24 months
- Preferred start date: Between December 1, 2025 and January 15, 2026
- Location: Mines Paris – PSL (Fontainebleau), with regular travel to Paris and Nice
- more details here
Desired skills and experience:
- Experience with common deep learning architectures (LSTM, Transformers, CNN) and decision tree methods (XGBoost, LightGBM, CatBoost, Random Forests)
- Experience working on clusters and high-performance computing environments
- Data visualization/dashboard development
- Physics-informed machine learning (ideal, but not required)
Specific details about the project will be discussed with candidates selected for an interview.
We would be grateful if you could share this opportunity widely within your networks and with any colleagues who may be interested.
For any questions, please contact:
Agnès Rivière – agnes.riviere@minesparis.psl.eu
Best regards,
Agnès Rivière
Associate Professor
Geosciences Center – Mines Paris – PSL
To apply:
Please compress all required documents into a single ZIP or PDF file and upload it to the following folder:
https://cloud.minesparis.psl.eu/index.php/s/TwMnIvNVJbobTvu
Application documents:
* CV
* Cover letter
* Diploma and academic transcripts
* Two letters of recommendation
* Publications and PhD thesis manuscript
