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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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spin-burst experiments, will complement advanced finite element analysis (FEA) in evaluating failure behaviour. Who we are looking for An enthusiastic, self-motivated, and resourceful candidate with a
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simulations for AI model validation. ✔ Artificial Intelligence (AI) & Deep Reinforcement Learning (DRL) for energy optimization ✔ Predictive Maintenance & Failure Analysis using Machine Learning and Physics
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rare inherited childhood mitochondrial disease. It is typically caused by changes in a gene known as POLG, resulting in a severe epilepsy, developmental delay and liver failure. The epilepsy is very
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analysis. You will compare the patient characteristics and approaches for the two surgeries to identify any difference between them and complete sub-analysis to evaluate failure risks. During the project
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failure due to high-cycle fatigue, reducing the efficiency and safety of the gas-turbine engines. The development of robust damper devices that reduce the vibration levels is of paramount importance
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failure before components are built? We invite applications for a fully funded PhD project to develop microstructure-aware simulation models for fatigue and damage prediction in turbine wheels. Working in
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circuits and electronics integration. It is desirable that the candidates have sound knowledge in statistical analysis of device output and have experience with failure analysis. The role holder will work
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of researchers. They will gain skills in: ✔ Artificial Intelligence (AI) & Deep Reinforcement Learning (DRL) for energy optimization ✔ Predictive Maintenance & Failure Analysis using Machine Learning and Physics
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high temperature corrosion rate involving mathematical models validated through simulation, experiments and analysis. Gas Turbines are used as a multipurpose power source in various applications like aviation, power