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stresses. Based on the experimental data, a semi-empirical model to be developed to assess insulation degradation and identify failure signatures that can inform future predictive asset management strategies
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of the studentship is to measure and model the optical properties of facial skin at different wavelengths and angles and to relate the results to other work by the research team on the clinical measurement and
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vehicles, data centers, etc.). These devices are mostly power electronic interfaced introducing new types of dynamic phenomena and the need for more detailed models, increasing complexity. In addition
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, multi-source learning is used to integrate diverse patient populations to build robust models, but having to protect sensitive information. Various modern ML paradigms are proposed to address the diverse
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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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transformer in operation. On the other hand, the Total Cost of Ownership (TCO) model is widely used to measure the whole lifetime cost of the transformer. In addition to the capital cost, cost of losses
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learning algorithm to develop an ability to choose what main data pattern/structure to preserve? This PhD project will approach this question by developing modelling strategies and pipelines to enable human
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(ACED) funded project under the Inequalities theme. ACED partners include the University of Cambridge, University of Manchester, UCL, DKFZ, OHSU, and Dana-Farber Cancer Institute. Main duties and
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The student will benefit from working alongside a multidisciplinary team of engineers, mathematicians, and physicists at the University of Manchester as well as a wide collaboration network within the UK and
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well as across the full life cycle. Expected Outcomes Development of aircraft energy consumption model(s) Adaptation and application of the model for different fuels and/or propulsion systems, and for different