PEPR AI launches a call for chairs to support scientific excellence in artificial intelligence

Part of the France 2030 investment plan, the National Strategy for Artificial Intelligence aims to structure a French AI research, innovation and training sector, based on scientific excellence, confidence and technological sovereignty. To meet these challenges, the CEA, CNRS and Inria, in close collaboration with the national public and private research community and the ANR, are coordinating the AI Research Program (PEPR AI). This structuring program aims to support cutting-edge AI research closely linked to societal and economic challenges.

As part of this dynamic, the PEPR AI is opening a call of “Chaires d'attractivité”, with the aim of attracting top-level researchers to France, who are currently working abroad, to lead ambitious scientific projects in French laboratories.

The aim of the call for chairs is to strengthen artificial intelligence research capabilities in France by enabling internationally recognized scientific talent to establish a long-term presence in the national ecosystem. Each Chair will receive funding of up to 1.2 million euros over a four-year period, covering the resources needed to deploy the project: salaries, operating costs, equipment, human resources, etc. 

Applications are open to:

• Junior or senior researchers;
• Currently working outside France, whatever their country of origin or practice;
• With an internationally recognized track record in the field of artificial intelligence;
• Proposing an original four-year research project supported by a French host laboratory, whether or not affiliated to PEPR AI.

The projects submitted must be in line with at least one of the scientific themes identified as priorities within the PEPR AI framework:

• Frugal AI: optimizing energy performance and the resources needed to train and use models;
• Embedded AI: designing AI solutions that can be integrated into devices constrained in terms of computing or mobility;
• Distributed AI: developing decentralized and collaborative approaches;
• Trusted AI: strengthening the reliability, explicability, robustness and ethics of AI systems;
• Mathematical foundations of AI: delving deeper into the theoretical and algorithmic foundations on which artificial intelligence is based.

Projects will be evaluated on an ongoing basis, according to a rigorous process that guarantees the scientific excellence of the selected applications. Candidates are therefore invited to submit their applications as soon as possible, in liaison with the host institutions.

To find out more about how to apply, and to access the full text of the call for applications: