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A continual learning approach for robust robotic control in electric batteries assembly. This project is an exciting opportunity to undertake industrially linked research in partnership with
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successes and proposes intelligent sensing and control solutions for automated robotic systems capable to be tele-operated using smart human-machine interfaces. This is an exciting PhD project that has a
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Open PhD position: Autonomous Bioactivity Searching Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 42-month funded PhD studentship will contribute to cutting
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Authority (UKAEA) to address key challenges in robotic deployment systems enabling repair automation. The successful candidate will be primarily based at the Rolls-Royce University Technology Centre in
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. This project will build upon our research and industrial successes, focusing on developing control solutions for automated robotic systems that can be teleoperated using intuitive human-machine interfaces
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workspaces under positional restrictions. Develop smart control algorithms that will allow the robotics end-effectors to communicate with the central control system and coordinate tasks with other end
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automated workflow for high-level quantum chemical calculations and we have generated thousands of examples relating to the reactivity of molecules for a specific chemical reaction. This project will evaluate
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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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that are highly controlled and potentially measured in milliseconds rather than seconds or minutes. This level of control will generate products with minimal side reactions and create the highest possible yields
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