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Field
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functional features that enabled them to respond to environmental cues, including temperature, pH, light, magnetic fields, and ultrasound. This project will develop the materials, methods, and designs
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validated surface functionalisation methods that significantly improve metascintillator performance, accelerating the development of advanced radiation detectors for ToF-PET and enhancing early cancer
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September 2026. The PhD will characterise the consequences of childhood encephalitis relative to acquired brain injuries & develop training to support understanding. Encephalitis is inflammation or swelling
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. However, there are significant challenges to a broad proof of concept that would be addressed in this PhD project. Laser beam sources, process development and control to enable better control of mass
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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to collaborate not only with peers in Swansea but also with partners across the UK fostering a rich and diverse research environment. Your role will be to develop robust remanufacturing process
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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, allowing them to add to their existing clinical targets of anxiety and depression disorders, thus developing impact from this research. Methodology This studentship will take a mixed-methods approach to
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treatments. To date, there are few techniques that integrate AI and digital twins to improve patient outcomes. Your Role In this project, you will develop new methods that combine AI and digital twins
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temperature within the engine environment. The aim of the proposed research is to develop modern primary atomisation models which better capture the atomisation physics associated with modern aerospace airblast