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have recently completed a systematic analysis of chemical retention and xenometabolism in mycobacteria (funding by the Gates Foundation) demonstrating that we can predict compound entry, retention and
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PhD Studentship: Open Radio Access Network (ORAN) for Distributed Edge Computing Orchestration in 6G
Magazine, 2024. "Traffic Prediction with Shared Causal Inference in ORAN Computing Continuum," IEEE Global Communications Conference (Globecom), 2024. "Cascade Network Stability of Synchronized Traffic Load
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), personality traits, appraisals, coping resources and social support networks in predicting the prevalence of mental health and well-being among soccer match officials. Understand soccer match officials' lived
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healthcare technology. Project Overview Healthcare digital twins are virtual replicas that continuously assimilate patient data to provide personalised predictions and support clinical decisions. To enable
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Magazine, 2024. "Traffic Prediction with Shared Causal Inference in ORAN Computing Continuum," IEEE Global Communications Conference (Globecom), 2024. "Cascade Network Stability of Synchronized Traffic Load
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predict the extent or nature of injury and future impairment. While CUS is portable and repeated scans can be undertaken at the cotside, they lack the spatial resolution of MRI. MRI, however, requires
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predict and rationalise XFEL observables are desperately needed such that XFEL results can reach their full potential. Aim This research aims to utilise the latest advances of computational methods (machine
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. Applicants for the studentship should ideally hold, or be predicted to achieve, a first-class undergraduate degree or equivalent in Psychology or related discipline. A relevant MSc (e.g., epidemiology
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on environmental, meteorological or physical conditions, in combination with satellite and / or climate data, can help make predictions for new, unseen conditions. The latter is particularly relevant when data is
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that are not seen in any other material. This project combines cutting-edge sampling techniques with machine-learned potentials for accurate phase predictions, offering considerable opportunity for method