This project is about developing reinforcement-learning based AI systems that directly interact with some segment of society. The applications include matching and other allocation problems. The research will be performed at the interface between reinforcement learning, social choice theory, Bayesian inference, mechanism design, differential privacy and algorithmic fairness. The research will have both a theoretical and practical component, which will include some experiments with humans. However, a good theoretical background in probability, machine learning or game theory is necessary for all students. The positions are available from January 2024. The PhD lasts for 4 years and includes a small teaching component.