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lead to increased NOx emissions to the environment, and therefore require the need for downtime and maintenance. Shape optimisation methods such as adjoint have been employed to create optimal designs in
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Machine tool dynamics-based digital twins for real-time monitoring of cutting tool conditions in smart manufacturing
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Development of Digital Twin Models for Real-Time Condition Monitoring of Electrical Machines in Electric Vehicle Applications
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Multi-Material Laser Powder Bed Fusion for Next-Generation Additive Manufacturing
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Intelligent Materials Health Monitoring: Utilising Machine Learning to Ensure the Long-term Stability of Perovskite Solar Cells
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to keep abreast of developments. Plan for specific aspects of the research programme as discussed with the fellowship supervisor. Contribute to research group planning. Coordinate and liaise with other
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. Some relevant experimental physics experience is desired but not essential. An interest in making photonic devices and strong analytical reasoning is desired. Some computational simulation experience and
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-Stokes equations and are technically the most efficient and accurate optimization methods applied to CFD problems. Depending on the student’s background on CFD, the general steps of the project steps
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Deadline: Applications accepted all year round Details CO2 capture and storage is believed to be a promising option for controlling CO2 emissions in the short to medium term. Several methods exist for CO2
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programme in this area at The University of Sheffield, led by the primary supervisor Dr Dan Geddes, and co-supervisor Dr Brant Walkley, in collaboration with Sellafield Ltd. and National Nuclear Laboratory