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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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spaces and habits for them. This is a highly interdisciplinary project that combines computational modelling and behavioural science. The first part will be based on the use of state-of-the-art
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discover therapeutic targets relevant to Welsh populations. You’ll also help translate your computational insights into lab-based validation using experimental models, paving the way for new diagnostics and
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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will
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for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and
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trends to provide immediate post-race feedback to Sport Directors that can be used to assess race strategy and tactics. Research, review and develop models based on objectives 1 and 2 to develop a race
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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Modern numerical simulation of spray break-up for gas turbine atomisation applications relies heavily upon the use of primary atomisation models, which predict drop size and position based upon
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Award Summary This is a 4-year studentship. Stipend of £18,873 (stipend may be uplifted subject to confirmation) and home fees are covered. Overview Interested in using your computational and
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diseases, but is frequently misunderstood, forgotten, and missed. As a toxic proteinopathy that leads to progressive fibrosis, it offers a powerful model for studying common pathways in CKD and represents a