Artificial intelligence has experienced enormous developments in the recent past around the world, with applications in many areas of science and industry. In recent years, machine learning and neural network methods have developed increasingly important links with statistical physics. The CNRS tenure-track position aims to support this interface, by recruiting a researcher developing sophisticated artificial intelligence techniques to solve statistical physics problems, or using tools from statistical physics to better understand and improve machine learning algorithms. Candidates must propose a research project which can be developed in one or more of the three host laboratories: Institut de Physique Theorique de Saclay (contact Pierfrancesco Urbani <pierfrancesco.urbani@ipht.fr>), Laboratoire Charles Coulomb Montpellier (contact Ludovic Berthier <ludovic.berthier@umontpellier.fr>), Laboratoire de Physique de l'Ecole Normale Superieure de Lyon (contact Pierre Borgnat <Pierre.Borgnat@ens-lyon.fr>).

Cordialement

Pierre Borgnat