Artificial intelligence for materials modelling towards responsible energy management

Lyon 1 University - Institut Lumière Matière; France; On-site; EUR 48,000 - 64,000; Full time

Job summary

The Institut Lumière Matière (iLM) at Lyon 1 University invites applications for a Researcher position in the MMCI team. The role focuses on developing AI-based methods to model materials at mesoscopic scales, with quantum-level accuracy and energy-efficient HPC techniques.

Collaboration across the Lyon ecosystem and with the DIAMOND platform is encouraged. The candidate will contribute to teaching activities within the Physics Department, from undergraduate to Master’s level, including

Responsibilities

• Lead research program in materials modelling using AI methods and machine learning to accelerate simulations.
• Secure competitive funding and foster collaborations across the Lyon research ecosystem, including interactions with the DIADEM DIAMOND platform.
• Teach across undergraduate to master’s programmes within the Department of Physics, including potential English-language Master’s-level courses.
• Develop courses on artificial intelligence and machine-learning methods applied to the physical sciences.

Job description

Organisation/Company Lyon 1 University - Institut Lumière Matière Department Physics Research Field Physics » Computational physics Researcher Profile Established Researcher (R3) Positions Other Positions Application Deadline 26 Oct 2026 - 16:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Summary of the scientific project:

The Institut Lumière Matière (iLM) is an internationally recognized research laboratory in physics and chemistry, combining fundamental research, innovation, and contributions to major societal challenges. It has developed integrated expertise in materials synthesis, characterization, and modelling, drawing in particular on numerical simulation and artificial intelligence.
The successful candidate will develop, within the MMCI team, a research program in materials modelling based on the development of artificial intelligence methods. They will develop machine-learning approaches to accelerate simulations and overcome current limitations in system size and timescale. The objective will be to model complex systems up to mesoscopic scales while retaining accuracy derived from quantum-level approaches. Research will focus in particular on nanostructured materials, van der Waals heterostructures, coordination polymers, and solid–liquid interfaces, with applications in energy-efficient electronics and in the storage, conversion, and sustainable management of energy.
The successful candidate will be expected to demonstrate the ability to conduct innovative research at the highest international level, secure competitive funding, and develop collaborations, particularly across the Lyon research ecosystem. They will establish their research within the MMCI team and may develop strong interactions with the DIAMOND platform of the DIADEM PEPR, thereby contributing to accelerating materials discovery.
The position lies at the interface of physics, materials science, numerical simulation, and artificial intelligence. The intelligent management of high-performance computing and the reduction of its environmental impact will require the development of advanced modelling methods capable of describing materials with quantum-level accuracy while limiting the energy consumption associated with computational workload.

Summary of the teaching project:
The Department of Physics has a strong policy aimed at supporting student success, based in particular on a competency-based approach, academic mentoring by designated faculty members, international openness, the development of professionally oriented programmes, and continuing education.
It offers a broad range of programmes in physics and related fields. The Department regularly upgrades its teaching laboratories, evaluates and develops its curricula, and contributes to interdisciplinary teaching.
The successful candidate will teach at all levels, from undergraduate to master’s programmes, within the courses coordinated by the Department of Physics, including lectures, tutorials, and laboratory classes.
Teaching may cover topics related to the candidate’s research activities, both at undergraduate level and within the Master’s programmes in Fundamental Physics and Applications and in Materials Science. The successful candidate may in particular contribute to the future “Quantum and Complex Light-Matter Physics” track. Part of the Master’s-level teaching may be delivered in English.
The successful candidate will also contribute to the development of courses on artificial intelligence and machine-learning methods applied to the physical sciences.