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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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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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Intelligent Materials Health Monitoring: Utilising Machine Learning to Ensure the Long-term Stability of Perovskite Solar Cells
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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
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year round Details Functional brain imaging methods such as functional magnetic resonance imaging (fMRI) have already revolutionized how we can study the processes and functioning of the healthy human