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with sufficient statistical justification to proceed, given the available population and resources. The recommendations will also provide a tailored framework for sample size calculations specific
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appropriate statistical testing to test the efficacy of the models. The project forms part of a wider effort for developing an effective VR HRI toolkit for improving interactive fluidity between robots and
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high-priority condition as new disease-modifying therapies are developed. This PhD tackles a key diagnostic bottleneck in ADTKD-MUC1 and integrates precision genomic medicine into routine kidney care
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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Applications are invited from UK students for a three-year PhD studentship funded by the NIHR Nottingham Biomedical Research Centre, School of Medicine. The PhD project is clinically focused towards
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analyse large datasets such as the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics to identify activity related to the treatment of community acquired pneumonia. This will require
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, statistics, sleep medicine, and artificial intelligence, for example. A very significant and specific benefit we can offer is the option for to complete a PhD in the 36-months, if you wish . The opportunity
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Deadline: 24.08.2025 Number of positions: 1 For UK students only This 3.5 year PhD project is fully funded for home students only. The successful candidate will receive a tax-free stipend set at
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Improving recovery from pneumonia after hospitalisation Project description: Applications are invited from UK students for a three-year PhD studentship funded by the NIHR Nottingham Biomedical
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early ‘prodromal’ stages) is yet to be established in large community settings. This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative