Postdoctoral Fellowship, Mathematical Statistical Physics Information Theory Theoretical Machine Learning

ICTP's QLS section seeks applications from outstanding scientists of any nationality with a strong research record for a postdoctoral position starting spring 2023. The position is linked to the project CHORAL on the Computational Hardness Of RepresentAtion Learning funded by the European Research Council, with Dr. Jean Barbier as Principal Investigator.

The QLS section provides a unique international research environment for postdoctoral fellows with about 15 group members, an intense program of workshops and conferences, close collaborations with local institutions (SISSA, ICGEB, Univ. Trieste) and internationally renowned ones (ENS Paris, EPFL, IPhT, UCSD, NTNU, MPIPKS, Aalto Uni, Toronto Uni, Minnesota Uni, etc). The QLS section has expertise in a broad range of fields including statistical physics of information processing, information theory, high-dimensional probability and statistics, statistical learning and inference, reinforcement learning, algorithms, stochastic processes and thermodynamics, theoretical ecology etc. Postdoctoral fellows are encouraged, and supported, to participate in activities in developing countries in order to promote the ICTP mission. The selected postdoctoral researcher is expected to carry out active, independent and multidisciplinary research in the broad area of: Statistical inference and theory of neural networks: statistical mechanics, random matrix theory, information-theoretic and algorithmic aspects.