Post-Doctoral Research Visit F/M Post-Doctoral Research Visit F/M Postdoctoral position on Theory of Learning in Games with Limited Information

id="offer-description" class="ecl-u-type-heading-2 ecl-u-mt-none ecl-u-mb-l">Offer Description In his/her journey of postdoc, the candidate will be supported by ANR JCJC project REPUBLIC and PEPR Foundry, and supervised by Debabrota Basu . Debabrota is affiliated with the Scool project-team (previously SequeL ) of Inria Centre at University of Lille. As a team, Scool is internationally recognised for developing theories and algorithms for sequential learning and decision making, i.e. in the fields of bandits and reinforcement learning. The candidate is expected to work on understanding impact of different types of structures on learning is sequential two-player games. The project is expected to simulate the existing and new collaborations with researchers and groups working on responsible AI, bandits, and reinforcement learning. The candidate will also be part of the HumAIn alliance that aims toward studying humane impact of deploying AI. From the application point of view, Scool is involved in multiple projects that incorporates medical data, agricultural data, and e-commerce. Depending on the future development, we will be interested to deploy such responsible AI systems and algorithms for securing such applications. To be specific, the postdoc will first investigate the fundamental question of impact of structures and constraints on imperfect information two-player games. The goal is to derive statistical characterisations and design efficient algorithms, when possible. Th