Job offer

Organisation/Company CentraleSupélec Rennes campus Department Smart Energy Department Research Field Engineering » Electrical engineering Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 29 May 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number ANR-25-CE Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The Smart Energy Department at the IETR Lab (UMR CNRS 6164) is opening a fully funded three-year PhD position to consolidate its research axis “Advanced tools for operation/supervision of energy networks” at the Rennes campus of CentraleSupélec.The position is funded as part of the French National Research Agency’s (ANR) FairGrid-AI project “Fair access for all to a low-carbon electricity grid unlocked by Artificial Intelligence”. The project aims at developing innovative methods to allow more equitable access to electricity grid capacity for all users, thanks to the use of machine learning tools and techno-economic analyses. This project is aligned with the sustainable development goals (SDG) 7 and 10 of the United Nations, by promoting a low-carbon, sustainable, and inclusive energy system. This project is part of an international collaboration with researchers from University College Cork in Ireland.

Where to apply

E-mail

Requirements

Research Field Engineering » Electrical engineering Education Level Master Degree or equivalent

Research Field Computer science Education Level Master Degree or equivalent

Research Field Economics Education Level Master Degree or equivalent

Skills/Qualifications

Candidates must hold a Master’s (M.Sc, M.Eng) degree in electrical engineering, energy or computer science with a focus on data science (knowledge of energy systems is a plus). The ideal candidate for the position has skills in electrical grid modelling (OpenDSS, Pandapower, MATPOWER, etc.), programming skills (Python, Julia, Matlab), as well as interest and/or experience in machine learning classification methods.