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Field
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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with inflation). Research training and support grant (RTSG) of £3,000 per year. Funding is available for 4 years. Closes: Open until position filled The overarching aim of this project is to find
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, enabling early detection of damage. Renewable Energy: Rapid, optimized design of wind turbine blades and structures for greener energy. Microstructures: Accurate, efficient analysis of devices like MEMS
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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Bhutan (covering 2013–present, at resolutions from 15-minute to daily). Objectives for this project are flexible, but include: Harmonising timestamps, units, and metadata across the seven national datasets
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that allow historical performance phenomena and training practices to be re-animated in the present moment in the form of a ‘live archive’. Project aims and objectives Using Reckless Sleepers’ extensive body
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Project details Early detection of cognitive decline allows identification of those at high risk of developing dementia when medical treatments may be effective in preventing disease onset. Our
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, offering a consistent, objective, and transparent framework for evaluating circularity performance. Most crucially, it facilitates the identification and evaluation of resource recovery opportunities
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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using thermographic Non-Destructive Testing (NDT), a critical method for ensuring aircraft safety and reliability. NDT is increasingly vital in the aviation sector, enabling the detection of hidden