584 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" PhD positions in United Kingdom
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supporting the setup, calibration, and running of laboratory experiments, including the preparation and configuration of sensors, data acquisition systems, and associated hardware and software components
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) Payment technologies and the future of money Explainable artificial intelligence (AI) in financial services Integration of FinTech and big data in financial markets and sustainable finance. To discuss the
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simulation experience; collaboration with leading researchers; and training in advanced characterisation, data analysis, and data interpretation. Number Of Awards 1 Start Date 1st October 2026 Award Duration 4
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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date 1 October 2026 Additional Funding Information This PhD project is funded for four years by Big C with a contribution of £50,000 supported by the John & Pamela Salter Charitable Trust. Funding
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information, please contact main supervisor; Prof Michael Greaney (michael.greaney@manchester.ac.uk ).
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the Birmingham MC40 cyclotron facility. This experimental campaign and the new data/insights will allow you to validate structural integrity models of ASSs linking meso- and macro-scales. During this PhD project
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with a wealth of social and networking opportunities. How to apply For further information please contact: Name: Prof. David MacManus Email: d.g.macmanus@cranfield.ac.uk Phone: +44 1234 754735 If you are
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reliability and maintenance strategies. Filter Rig: An experimental setup to study filter clogging phenomena, allowing for the collection of data to develop and validate prognostic models for filter
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mitigating jamming and spoofing threats in real-time. Integration of Trusted Execution Environments (TEEs): Investigate the use of TEEs to create secure zones within embedded systems, facilitating secure data