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Field
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improves the performance of ROMs, making them more applicable to real-time structural health monitoring, vibration analysis, and control design. This research offers real-world impact across several
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the MET office. The student could choose to develop these connections to understand resident experience and behaviours, identify the current barriers and facilitators, to inform adaption measures
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-funded Swansea University Research Excellence Scholarship (SURES) for a full-time doctoral student commencing in October 2025. Investigating functional genomic and multi-omic data analysis and integration
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performance and university-specific criteria. Integrating multimodal analysis (voice tone, facial expressions, sentiment analysis) for holistic assessment. Ensuring fairness and bias mitigation in AI-driven
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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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factors (learning curve). These will be linked with the CCTA imaging biomarker data (quantitative plaque analysis) that is being collected as part of the EU HORIZON TARGET study to determine personalised
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AI approaches have recently been used to detect Alzheimer’s disease from CFPs among those with established disease (in case-control studies), the use of such approaches to predict disease (i.e., in
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with a surface. This project will involve using and further developing both the experimental and data analysis methods that are currently used within the research team. The student will learn how to use
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permanent magnet electrical machines are pushing performance boundaries. A major challenge is the structural integrity of the carbon-fibre reinforced polymer (CFRP) sleeves used to contain the rotor’s magnets
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performance will be assessed using finite element analysis and experimental work. Additionally, life cycle assessment will be performed to quantify environmental and economic impacts. This project is intended