Post-doctoral Researcher Physics-informed artificial Intelligence for hydrogeological modeling

IMT Mines Alès; France; Sur place; EUR 30 000 - 41 000; Plein temps

Avantages offerts par ce poste

Vacation time

Public transport support

Mobility allowance

Innovation ecosystem

Sea & mountains nearby

Résumé du poste

IMT Mines Alès invites applications for a 13‑month, full‑time postdoctoral position focused on Physics‑Informed Machine Learning for groundwater forecasting in the Lez/Roussillon system. You will join the CREER center and the HSM unit, contributing to the PREV’IA project.

Minimum: PhD in hydrogeology, hydrology, or environmental modeling, with experience in ML for complex natural phenomena and strong teamwork. Proficiency in scientific English is required.

Qualifications

• PhD in hydrogeology, hydrology or environmental modeling.
• Experience in machine learning for modeling complex natural phenomena.
• Ability to work in multidisciplinary projects and teams.
• Strong command of scientific English.

Responsabilités

• Apply Physics-Informed Machine Learning approaches to hydrogeological modeling.
• Develop Physics Informed Architecture and Physics Informed Loss Function concepts.
• Collaborate across teams and contribute to project documentation and dissemination.

Connaissances

Machine learning

Hydrogeology

Multidisciplinary collaboration

Scientific English

Formation

Ph.D. in hydrogeology / hydrology / environmental modeling

Description du poste

Organisation/Company IMT Mines Ales Department Human Ressources Department Research Field Geosciences » Hydrology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Nov 2026 - 00:00 (UTC) Country France Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Jan 2027 Is the job funded through the EU Research Framework Programme? European Union / Next Generation EU Is the Job related to staff position within a Research Infrastructure? No

Offer Description

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 (CREER), and artificial intelligence and industrial and digital engineering (CERIS). It has 12 technology platforms and 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.

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

Internal Application form(s) needed

FP - Post-doctoral Researcher PREVIA PIML.pdf

So join us and enjoy these many benefits:

• Generous vacation time
• 75% of public transportation costs covered
• Sustainable mobility allowance for carpooling or biking
• A vibrant innovation ecosystem (startups, students, research, companies, and more)
• Ideal environment for pursuing your passions (sea/mountains nearby)

Eligibility criteria

The position offered by IMT Mines Alès is a 13-month, full-time, fixed-term contract, under public law under the provisions of the management framework of the Institut Mines-Télécom, profession P, Post-doctoral fellow, category II.

Salary:

€35,542 gross per year

Selection process

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