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Field
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, which complements our current robotics infrastructure and fills a gap in mammalian system development. Additionally, the fellow will mentor trainees and support the lab’s growing efforts in open-source
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, for example in human and robotic exploration vehicles (orbiters and landers) and space transportation systems (launchers, re-entry vehicles and space tugs), as well as orbital systems for in-orbit servicing
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workflows and validate the established systems in tandem with clinical partners. About You You will possess a PhD (or be nearing completion) in mechanical, electrical, or biomedical engineering, or a related
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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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The Robot Learning Lab in the Department of Computing at Imperial College London is seeking a talented Research Assistant (pre-doc) for an ambitious new project on dexterous robot learning. In
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Laboratory (ORNL) and Department of Energy (DOE) mission. Selection will be based on qualifications, relevant experience, skills, and education. This position resides in the Manufacturing Robotics and Controls
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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, the Associate will assist with research and development projects in the areas of robotics, machine learning, control systems, and/or computer vision. They will be responsible for: designing and analyzing
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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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, Intelligent Manufacturing and Robotics, Communications Systems and Sensing, Nuclear Engineering, Advanced Materials, Membranes and Water Security, Smart Mobility and Logistics, Refining and Petrochemicals