The Dynamics team at MERL is looking for an enthusiastic and qualified individual to undertake research in safe robust reinforcement learning (RL). The perfect candidate should have a comprehensive background in RL, for example, Constrained Markov decision processes (CMDPs) and Robust MDPs theories. Familiarity with dynamical system theory and nonlinear control theory is an advantage, but not mandatory. It is expected that the results generated during the internship will be submitted, for instance, to ICML/ICLR/NeurIPS. The internship is projected to last 3 months with a flexible start date.
Research Areas: Control, Dynamical Systems, Machine Learning
Contact: Mouhacine Benosman
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