You investigate how agents learn through interaction, simulation, and structured feedback, represent also manipulate knowledge in compositional forms, as well as integrate reinforcement learning with symbolic abstractions, hierarchical planning, memory, and reasoning. o excellent MSc in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Systems Engineering, or related fields + ability to design and analyze systems that act in complex environments and improve through interaction, simulation, or structured feedback + experience with structured engineering artifacts (e.g. requirements, system models, simulations, or formal specifications) is an advantage
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