Post-doctoral Researcher Physics-informed artificial Intelligence for hydrogeological modeling - 13-Month Fixed-Term Contract - IMT Mines Alès

Come join IMT Mines Alès, a prestigious “grande école” ranked among the top engineering schools both nationally and globally, located in Alès—a welcoming, livable city and the capital of the Cévennes region, where residents highly value the quality of life.

Founded in 1843, IMT Mines Alès currently has 1,400 students (including 250 international students) and 380 staff members. The school has three high-level scientific and technological research and teaching centers, working in the fields of materials and civil engineering (C2MA), the environment and risk management (CREER), and artificial intelligence and industrial and digital engineering (CERIS). It operates 12 technology platforms and has 1,600 partner companies. For more information: https://www.imt-mines-ales.fr

You will be affiliated with the Center for Research and Teaching in Environment and Risks (CREER) at IMT Mines Alès and the HSM research unit.

This work is part of the PREV’IA project, which focuses on understanding and forecasting water resources in the Pliocene-Quaternary aquifer of the Roussillon Plain and the Lez spring that supplies Montpellier with drinking water.

Your work will build upon an ongoing thesis within the UMR HSM (HYTAKE team), focusing on the sustainability of the karst water resource (Lez aquifer) supplying a Mediterranean metropolis (Montpellier) in the context of climate change.

Your mission:

• Use emerging concepts in “Physics-Informed Machine Learning” (PIML) approaches to assess the potential benefits of synergy in hydrogeological modeling: (1) concept-based modeling on the one hand, and (2) neural networks informed by, or complemented with, physics on the other. The PIML (Physics Informed Machine Learning) approach is being developed along two lines: (i) Physics Informed Architecture (PIA): integration of physical knowledge into the model architecture (hidden layers); and (ii) Physics Informed Loss Function (PILF): combining physical modeling (differential equations) and black-box methods, merged into the cost function (regularization term). Both methods may be explored. The proposed models may be used to determine the evolution of certain hydrological variables in response to climate change.

You can find more information in the job description below:

https://partage.imt.fr/index.php/s/R3Dr7Cf2q8972tc

Minimum education and/or experience required:

• Ph.D. in a field related to hydrogeology, hydrology, or environmental modeling

Required skills, knowledge, and experience:

• Experience in machine learning for modeling complex natural phenomena

• Ability skills in multidisciplinary projects

• Genuine ability and experience in organization and teamwork: organizing meetings, planning activities, contributing to the drafting of administrative documents

• Good command of scientific English

Additional information:

13-month fixed-term contract under public law - Position open to civil servants and contract employees

Information for internal use intended for staff on the IMT Management Framework:

Reference job category: II - P

This position is open to all. IMT Mines Alès is committed to providing the necessary accommodations for people with disabilities to ensure an inclusive and accessible work environment.

Salary: €35,542 gross per year.

Application deadline: November 1, 2026

Estimated date of the selection committee meeting: November 23, 2026

Desired start date: January 1, 2027

We strongly recommend contacting the individuals listed below under the “Job Description” section

Contacts:

Regarding the job description:

Anne JOHANNET, PREV’IA Project Manager

Juliette CERCEAU, HSM Liaison

Hervé JOURDE, HSM-HYTAKE

For administrative matters:

Géraldine BRUNEL, Director of Human Resources

So join us and enjoy these many benefits:

• Generous vacation time

• On-site dining

• 75% of public transportation costs covered

• Sustainable mobility allowance for carpooling or biking

• Stimulating innovation ecosystem (startups, students, research, companies...)

• Ideal environment for pursuing your passions (sea/mountains nearby)