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partners and test centres. Physical testing, such as controlled spin-burst experiments, will complement advanced finite element analysis (FEA) in evaluating failure behaviour. Who we are looking
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, such as centrifugal forces, bending, and thermal stress. You will work closely with the PEMC and Composites Research Groups, industrial partners and test centres. Physical testing, such as controlled
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markers. Develop machine learning models capable of predicting Category 1 emergencies based on real-time audio features extracted from calls. Work iteratively with YAS researchers to test and refine
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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this testbed available to users for testing hardware and applications. NPL will lead on the testing and security evaluation of the testbed and collaborate widely on the technology development. The student’s
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skills is referred as the following: An overall score of 6.5 or higher in the International English Language Testing System (IELTS, academic version); or A score of at least 237 on the computer-based form
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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family-friendly university. We welcome applications from candidates with disabilities. If multiple candidates prove to be equally qualified, those with disabilities or with equivalent status pursuant
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Academic score of 6.5 (with no less than 5.5 in each component test area) or equivalent. The studentship is supported for 3 years and includes full Home tuition fees plus a stipend of £19,215 per annum 2025
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multidisciplinary project applying chemical synthesis and biological testing to design, synthesise and biologically evaluate new small molecules which can interfere with arginine-dependent tumours. The general