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adaptation of the mesh during simulation to resolve and track features in the flow. The focus of your PhD would be on developing novel algorithms to efficiently redistribute and rebalance the parallel
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project aims to develop state-of-the-art computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the
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mission. You will: Help collate data resources relevant to suicide and self-harm. Develop new machine learning methodologies (from artificial neural networks, decision trees, evolutionary algorithms and
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person. Aims: The project aims to develop and evaluate AI methods for medical image analysis to detect diabetic retinopathy, glaucoma, cataract and age-related macular degeneration (AMD). As
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) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
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instrumentation of the structure, whilst effective, can be logistically expensive to implement for the entire network. To address these challenges, the project aims to develop a novel, population-based indirect
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, the project will develop algorithms for ecological sensing, adaptive motion planning, and energy optimisation under real-world constraints. Scaled experiments and high-fidelity simulations will validate system
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behaviour in a practical, real-time monitoring system requires advances in both sensor engineering and behavioural data interpretation. This PhD project aims to develop a next generation environmental
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
: Algorithm Validation and Use Case Demonstration (Months 27–36): This WP will first develop an integrated hardware–software testbed to systematically validate the performance of proposed solutions under
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-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in