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treatments. To date, there are few techniques that integrate AI and digital twins to improve patient outcomes. Your Role In this project, you will develop new methods that combine AI and digital twins
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(CAD) since 2016 and CT- Fractional Flow Reserve (CT-FFR) as a second line test since 2017. In 2018 a national health technology programme funded CT-FFR utilisation with the aim of improving patient
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for next-generation gas turbines. These geometries pose manufacturing challenges, particularly regarding heat transfer, microstructure evolution, and defect prevention. Building on recent doctoral research
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development could be foreseen in Year 4. The recruited PhD candidate will become a member of an active research group working on the development and application of cutting-edge computational techniques
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
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plausible future climate, land use changes and socioeconomic development scenarios e.g. urban planning. The outcome will provide a holistic assessment of flood risk for future strategies and climate
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treatments. To date, there are few techniques that integrate AI and digital twins to improve patient outcomes. Your Role In this project, you will develop new methods that combine AI and digital twins
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rolling basis, so apply early for the best opportunity to be considered. How To Apply Apply online by clicking the 'Apply' button, above. Select programme type (Research), 2025/26, Faculty of Engineering
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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signs of cardiovascular changes, adaptively model physiological patterns, and identify predictive biomarkers of maternal health. You will develop and apply cutting-edge techniques in: Signal processing