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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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aforementioned tasks with the following actions: Develop the principles and theories for governing the scalability principles for building innovative robotics end-effectors that can access geometrically complex
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leverage advanced bespoke continuum robotic systems to demonstrate the feasibility of applying the proposed coatings can be deployed in-situ. Ultimately, this work bridges the gap between the theory
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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites
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into hydrogen and nitrogen under practical onboard conditions. Successful candidate will develop and apply computational methods, such as density functional theory based atomistic modelling and machine learning
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respond over time (e.g. changing shape), controlled by the arrangement of differential materials within them. The goal of this project will be to develop responsive 4D-printed biomaterial devices for drug
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Deployment The PhD programme offers: Training in the theory for solar energy technologies, experimental measurement and evaluation techniques, tools for modelling and predicting PV generation. Opportunities
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-controlled structural colours that respond to stimuli. You will develop the materials, methods, and designs necessary to 3D-print the next generation of structural colour devices, integrating optically- and
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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