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entrants without historical data for their land use technology differently compared to those with established practices? This interdisciplinary project offers the chance to contribute to multiple fields
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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
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of novel AM materials on corrosion response of key component and develop a model to predict their behaviour. To address the goals set for tackling international climate change, the power sector needs
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Santos, Dr RG Bryant, Dr Chris Bousfield Application Deadline: 31 October 2025 Details We are seeking a motivated PhD candidate to develop innovative artificial intelligence methods for plant species
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compatibility with traditional composite matrices. Explore complementary computational fluid dynamics-discrete element method (CFD-DEM) simulations as a tool to predict fibre-fluid interactions and inform
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enhancers at repetitive GGAA DNA elements (GGAA microsatellites). These neo-enhancers appear to contribute to tumorigenesis and eventually tumour progression and possibly underlie germline variation
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. Early diagnosis and an accurate characterization of disease progression are critical for treatment and improving patients' quality of life. However, current methods rely on expensive and time-consuming
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energy consumption while balancing multiple, often conflicting requirements, such as comfort, cost efficiency, and sustainability. Effective decision-making in such a system requires continuously
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vapour deposition (CVD) remains a leading method for CNT synthesis, yet the role of catalyst composition in controlling CNT morphology and purity is still not fully understood. This PhD project, in
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Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD project description: Inkjet printing allows multiple materials to be 3D-printed