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for the company, which will open new markets and opportunities. This PhD covers a wide range of skills and so it is essential the candidate has a 1st degree in electrical engineering or equivalent experience
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been filled. Electrical treeing is a primary degradation mechanism in polymer insulation leading to the ultimate failure of high-voltage (HV) cables. Despite being a phenomenon first observed and studied
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challenge. This project aims to increase the technology readiness level of microwave NDE by addressing fundamental laboratory challenges and transferring techniques to practical use. The project involves
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(CHF) phenomena – the prediction of which is key to safely designing and operating water based nuclear reactors. Current industrial modelling tools necessitate excessively conservative safety margins
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
nature makes them susceptible to complex damage modes like delamination, fibre breakage, and matrix cracking, especially under high-velocity impacts from projectiles or debris. Current assessment
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undergraduate degree relevant to each individual project, e.g., Experimental Psychology, Physics, Neuroscience, Computer Science, Electrical Engineering, or a related subject. In addition, an appropriate master’s
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in numerate, computational, or environmental subject areas. Numerate Subject Areas include e.g.: Mathematics, Statistics, Physics, Economics, Finance, Engineering (Mechanical, Electrical, Civil, etc
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should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. To apply, please contact
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coal mining heritage, with hundreds of abandoned and flooded mine seams. Current groundwater levels are the highest ever recorded, and are rising due to the cessation of mine water pumping and climate
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to create molten salt MLIPs, predicting a variety of industrially pertinent properties: thermal conductivity, heat capacity, viscosity, and thermodynamic phase data. We will develop new statistical mechanical