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Bayi Glacier in Qilian Mountain, China (Credit: Xiaoming Wang, distributed via imaggeo.egu.eu)

Job advertisement Postdoctoral Position in AI for Water Temperature Modeling – Clim’Seine Project (Mines Paris – PSL)

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Postdoctoral Position in AI for Water Temperature Modeling – Clim’Seine Project (Mines Paris – PSL)

Position
Postdoctoral Position in AI for Water Temperature Modeling – Clim’Seine Project (Mines Paris – PSL)

Employer
Mines Paris logo

Mines Paris

And about us! Working at Mines Paris also means:
* Joining a prestigious institution with a rich history
* Playing a part in the digital transition and the transition to carbon neutrality to tackle the
climate emergency
* Belonging to PSL University, ranked 41st in the Academic Ranking of World Universities
* Up to 47 days of annual leave
* Meal vouchers valued at €11.52, with 60% covered by the employer

Homepage: https://www.cma.mines-paristech.fr/?lang=en


Location
Paris, France

Sector
Academic

Relevant division
Hydrological Sciences (HS)

Type
Full time

Level
Entry level

Salary
32000 - 42000 € / Year

Required education
PhD

Application deadline
15 November 2025

Posted
23 September 2025

Job description

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


How to apply

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