About the research centre or Inria department

Contract type: Fixed-term contract (renewable). Location: Villeneuve d'Ascq, Inria Center at the University of Lille. Starting date: 2026-10-01. Duration: 12 months.

About the research centre

Created in 2008, the Inria center at the University of Lille employs 360 people, including 305 scientists in 16 research teams. Recognized for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria center maintains a close relationship with large companies and SMEs. By fostering synergies between researchers and industry, Inria contributes to the transfer of skills and expertise in digital technologies and provides access to the best of European and international research for innovation and businesses, particularly in the region.

For over 10 years, the Inria center has been at the heart of Lille's university and scientific ecosystem, as well as FrenchTech, with a technology showroom at EuraTechnologies, a site of economic excellence dedicated to information and communication technologies (ICT).

Context

This postdoctoral position is part of a project funded by the PGMO program (Gaspard Monge Program for Optimization and Operations Research). It aims to develop new modeling and optimization methods to address the challenges of the energy transition. The project lies at the intersection of operations research, mathematical optimization, game theory, and artificial intelligence, with applications to electricity markets. The work will be conducted in collaboration with academic researchers and industrial partners, notably EDF, to develop decision-support tools for energy policy.

Responsibilities

This project examines the investment decisions of electricity generators in decentralized markets subject to uncertainty. It models interactions among generators using stochastic equilibrium games that incorporate long-term contracts, such as capacity mechanisms and contracts for difference (CfDs). The goal is to better understand how these contracts influence investments and the composition of the energy mix.

The project combines two complementary approaches: optimization methods based on complementarity problems and multi-agent learning techniques. The latter allow for approximating equilibria when models become too complex for classical methods. The research also takes into account market power, risk aversion, and the presence of multiple equilibria. Finally, the models will be applied to real-world cases, particularly island power systems, to assess the economic impacts and implications for energy policies.

Main activities

• WP1 – Model Development: Incorporate long-term contracts, uncertainty, risk, and market power into a stochastic equilibrium model.
• WP2 – Algorithm Development: Design and compare multi-agent learning methods to calculate equilibria in complex electricity markets.
• WP3 – Economic analysis: Evaluate the impact of different contracts on investments, the energy mix, and market efficiency using real-world case studies.
• Validation: Compare the new approaches to traditional optimization methods in terms of accuracy, robustness, and scalability.
• Dissemination: Publish the results in scientific conferences and journals, in collaboration with industrial partners such as EDF.

Requirements

The candidate must hold a Ph.D. in applied mathematics, operations research, or optimization.

• Solid knowledge of mathematical optimization, game theory, or operations research.
• Strong skills in mathematical modeling and algorithm development.
• Interest in machine learning, particularly multi-agent learning, or a willingness to develop skills in this area.
• Experience with electricity markets, energy systems, or optimization under uncertainty is a plus, though not required.
• Proficiency in at least one scientific programming language (Python, Julia, MATLAB, or equivalent).
• Ability to conduct research independently while working effectively within a multidisciplinary team.
• Strong writing and scientific communication skills in English (written and oral), sufficient to publish in international journals and present work at conferences.
• Motivation to collaborate with academic and industrial partners and contribute to the development of decision-support tools for the energy transition.

Benefits

• Subsidized meals
• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities
• Access to vocational training
• Social security coverage

Pay

€2,788 gross per month