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position is associated with the Robot Navigation and Perception Lab (https://rnp.aass.oru.se ) which belongs to the Centre for Applied Autonomous Sensor Systems (AASS) research environment (https
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Robot Learning (ID: TUEILSY-POSTDOC20251219-RL) Robots that learn from data promise greater autonomy and performance, but their deployment in the real world hinges on the ability to guarantee safety
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group aims to bring fundamental changes in the way the sensors and electronic devices are developed using materials designed for sustainability, and resource efficient printed electronics on flexible
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-on experience with robotic hardware (e.g., robot arms, tactile sensors) Familiarity with model-based planning approaches, robot force/motion control, and reinforcement learning Proficiency in programming (C
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, or decision-making in autonomous driving or robotic systems Reinforcement Learning and Agentic Control: Hands-on experience with reinforcement learning, multi-agent systems, or planning-based agents
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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is performed within nanophotonics, lasers, quantum photonics, optical sensors, LEDs, photovoltaics, ultra-high speed optical transmission systems, bio-photonics, acoustics, power electronics, robotics
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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entities, such as robots, vehicles, or sensors, forms internal representations of space, time, and motion when interacting in complex non-stationary environments. The objective is to study and develop models