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will lead the development of novel motor topologies optimised for this cutting-edge material. Supported by experienced supervisors, the student will be able to design, model, and validate working
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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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of deep learning models, especially when new training experiences are corrupted. The framework will be validated in robotic control scenarios during EV battery assembly, under process variations such as
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an assessment of the part quality; this will involve the development of laser beam processing on specific aerospace materials, and a model to understand the fundamental mechanisms of the process to identify
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effectors (https://www.youtube.com/watch?v=A_CTqVFJ7Jc). At the Rolls-Royce UTC, we have a unique capability to design, model, and develop robotic systems tailored for operations in restrictive environments
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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop