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Deadline extended: 30 October 2025 (originally 29 September 2025) A fully funded 3-year PhD is available in the School of Computer Science and Engineering (SCSE), Bangor University. The project will
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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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the Crick’s clinical PhD programme. About the Fellowships: This fully funded three-year PhD programme offers talented clinicians the opportunity to pursue biomedical discovery research in a world-class research
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by researching and learning abroad as part of your PhD programme Preparation for a prestigious academic or research career Option to choose our Behavioural Science pathway. Course details: The MRes/PhD
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for mechatronics engineering work Working experience Application form and interview Competencies, Skills & Knowledge Ability to conceptualize problems and develop well-reasoned and logical viewpoints Fluent (verbal
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: Functional genomics and psychiatric epidemiology Clinical informatics and data harmonisation Co-production and participatory research methods Working within a cutting-edge UK-wide data infrastructure
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of Sciences. We are a member of the Vienna Center for Quantum Science and Technology (VCQ), one of Europe’s largest hubs for quantum science, and of the Austrian Cluster of Excellence quantA, which supports
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of Sciences. We are a member of the Vienna Center for Quantum Science and Technology (VCQ), one of Europe’s largest hubs for quantum science, and of the Austrian Cluster of Excellence quantA, which supports
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across different imaging devices, including future sensors with unknown spectral sensitivities. Training The student will be based at the Colour & Imaging Lab at the School of Computing Sciences which has
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optomechanics, this project aims to deliver proof-of-concept quantum acceleration sensors ready for technological adoption. [1] Gonzalez-Ballestero et al, Science 374, 6564 (2021) [2] Piotrowski et al, Nature