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PhD Studentship: Designing Human-AI Teams for Meaningful Human Control of 'Machine-Speed' Operations
be applicable to command teams working in uncertain and information-degraded environments. Meaningful human control is necessary when humans have to be retained in or on the loop. This requires the AI
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. Our Team is part of the Quantum Science group of the Faculty of Physics. We are member of the Vienna Center for Quantum Science and Technology (VCQ), one of the largest quantum hubs in Europe, and of
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systems, sensing, wireless technologies and bio-inspired engineering. The successful applicant will focus primarily on the RF, high-frequency and experimental characterisation of externally fabricated
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in partnership with SMS Group, a world-leading supplier of metallurgical plant and rolling mill technology. Project: Closed-Loop Electromagnetic Microstructure Control During Hot Strip Mill Run-Out
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Join us! Are you a curiosity-driven scientist with a background in physics, engineering, or a related discipline, who wants to lead work at the intersection of robotics and metamaterials? Join us
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Position Summary: Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Control and Power Research Group, Department of Electrical and Electronic Engineering
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is suited to candidates with a PhD awarded or close to completion (or equivalent experience), in electrical machines, drives, control, real-time simulation, or a closely related engineering discipline
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We are seeking a creative and highly motivated Research Assistant/Associate to join Dr Somenath Bakshi's research group in the Department of Engineering. The project will investigate how bacterial
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control strategies. Current steel processing typically has very tightly controlled processes with little variability and control approaches optimised to minor changes. The combined challenges of cost
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Engineering at the University of Sheffield. A leading centre for machine learning, robotics, and autonomous systems. The student will join a research group working at the interface of machine learning, control