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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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candidates to work with our interdisciplinary and collaborative team on a project on research and development of innovative surface treatments of advanced engineering materials. You will be based in Manchester
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board development to support local AI in ATMs for enhanced security. Please note, this is open to home students only. PhD Studentship:cyberQuarter. The Studentship is available for an October 2025 start
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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of health economics researchers based at the University of Oxford’s Nuffield Department of Primary Care Health Sciences (NDPCHS). The successful candidate will help develop and deliver a portfolio of health
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sensor spoofing. These attacks manipulate input data while maintaining apparent operational normality, potentially leading to unsafe decisions without detection. This project aims to develop a novel
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interdisciplinary team working on the development of cross-platform alignment technologies that integrate material science, process engineering and sustainability analysis to deliver scalable solutions for circular
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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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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
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(i.e. red agents). However, due to a fragmented market, rapid technical developments, and nascent research the extent of capabilities and optimal solution architectures are not well understood. Current