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Field
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will focus on the development of voice analysis technologies to enhance the prediction and triaging of Category 1 ambulance calls. Ambulance call centres play a critical role in triaging life-threatening
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on health and use economic methods to evaluate relative costs and benefits. This may include use of health impact assessment methods, statistical analysis of secondary data sources to estimate health impacts
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evaluation, policy advocacy, or better understanding the contexts and causes of such abuse. The student will use advanced data science and applied statistics to enable combined analysis of different modes
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improves the performance of ROMs, making them more applicable to real-time structural health monitoring, vibration analysis, and control design. This research offers real-world impact across several
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environmental stressors, in particular heat, and patterns of violence in the UK. This project will largely use quantitative methods to explore the relationship between climate change and violence. A key component
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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You will lead the qualitative work to understand how individuals experienced the intervention and app how it worked. This will directly impact the design and refinement of the intervention, and so
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that require treatment while reducing unnecessary detection of slow-growing cancers. You will play a key role in a large mixed methods project as a qualitative researcher conducting focus groups, interviews and
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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the MET office. The student could choose to develop these connections to understand resident experience and behaviours, identify the current barriers and facilitators, to inform adaption measures