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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
in machine learning methods for pattern recognition and prediction. An academic or practical background in sleep science and/or elite sport is highly desirable. The candidate will be embedded within
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contexts, for example to help understand and predict the performance of polysaccharides in food systems and drivers of polysaccharide evolution (manuscript attached). Once promising candidate polymers have
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will also include evaluating and validating existing numerical models, ensuring their reliability in predicting real-world conditions. This project is supported by brand-new laboratory facilities
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antibiotic mixtures across temperature scenarios in diverse freshwater bacteria. This research aims to improve predictions of how combined stressors influence bacterial communities and broader ecosystem
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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challenges to the electricity transmission and distribution system, as solar power is not dispatchable and therefore its incorporation as a major element of the generation mix requires the accurate prediction
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predictive maintenance. Gas turbine diagnostics and prognostics has been progressed quickly in recent years and are crucial technologies to predict the health of gas turbine systems and support the predictive
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, a state-of-the-art process-based model for groundwater risk assessment and contaminant transport modeling. By improving predictive modeling of transient contaminant source terms, this research will
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the accurate prediction of reaction enthalpies and activation free energies for all relevant intermediates. In this project, a deep learning and generative design toolchain will be developed resulting in an ML
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perpetuation (or maintenance/persistence); to build ML models that include the heart’s physical properties to find patterns in the data and predict which areas in the heart drive AF. This project will explore