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, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform statistical analyses to assess stability and plasticity of multisensory
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processing, or optimisation to turn heterogeneous knowledge (channel/network state, maps and topology, mobility, hardware constraints, and task-level KPIs) into reliable and efficient decisions. The work spans
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fuels (hydrogen, methanol, ammonia), simulation tools for marine engines and/or fires due to fuel leakages, data analysis methods and their applications for ships, sufficient understanding of appropriate
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visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
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the models, ensuring usability, reliability, and integration into operational workflows. The successful candidate will benefit from interdisciplinary training in experimental design, advanced speech analysis
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The abuse of older people is one of the most abhorrent, growing, yet under-researched problems in modern society. Among the reasons for this is the lack of reliable datasets to understand the scale
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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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emissions and sustainable aerospace engineering. Motivation The reliability of electric propulsion systems is pivotal for next-generation energy and aerospace solutions. In particular, surface-mounted
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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simulations and finite element analysis, with high-heat flux electron beam experiments. The research will simulate and replicate steady, cyclic, and transient thermal loads to better understand PFM behaviour