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, Electrical Engineering, Aerospace Engineering, or a related field. Control Theory: Strong theoretical and practical background in control systems, including PID, LQR, MPC, or adaptive control. Robotics
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people. By embracing diversity, we believe science can achieve its fullest potential. THE ROLE During your internship you will work on a projectin the Event-Driven Perception for Robotics(https
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, Princeton Robotics; Associated Faculty, Computer Science) and include opportunities for collaboration across Princeton Robotics labs. Appointments are for one year, with the possibility of renewal contingent
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by supervisor. Requirements Bachelor’s degree or higher in Robotics, Computer Science, Mechanical Engineering, Control Engineering, or a related field. Experience in imitation learning and
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and cognition, humanoid technologies and robotics, artificial intelligence, nanotechnology, and material sciences, offering a truly interdisciplinary scientific experience. Our approach integrates
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physics to investigate the emergent dynamics of active matter. The work will combine experimental methods (robotics, machine vision, control, ...) with theoretical approaches from non-equilibrium
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will involve model training, test rig set-up, and experimental validation Job Requirements: The candidate must at least have a Master Degree in AI, Robotics, Automation, Mechanical Engineering, Control
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA DELL'ENERGIA ELETTRICA E DELL'INFORMAZIONE "GUGLIELMO MARCONI" | Italy | 4 days ago
control theory and AI-enabled methods. The activity will be carried out within the ACTEMA research group (https://dei.unibo.it/en/research/research-groups/actema ), in collaboration with other entities and
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, we believe science can achieve its fullest potential. THE ROLE During your internship you will work on a projectin the Event-Driven Perception for Robotics(https://edpr.iit.it/ ) group, coordinated by
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. Candidates should demonstrate technical proficiency in one or more of the following areas: Embodied AI and robot learning Vision-language-action (VLA) or multimodal AI modeling Perception, control