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Lead Supervisor name: Andrew Callaway, email: acallaway@bournemouth.ac.uk Project description: This PhD programme will determine the most clinically acceptable methods for emergency response teams
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The project: We invite applications for a fully funded PhD studentship in the Solid Mechanics Group at the University of Bristol to work on the predictive modeling of hydrogen-induced damage in
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emerging photonic microdevices promising to revolutionise computer, communication, and sensing technologies must be performed with unprecedented picometre (one-hundredth of the atomic size) precision
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Applications are invited for a PhD position at the University of Nottingham addressing the behaviour of thin foil materials for aerospace forming applications. The successful candidate will have a
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early ‘prodromal’ stages) is yet to be established in large community settings. This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
Overview: Cranfield University invites applications for a fully funded 3-year PhD, supported by the EPSRC DTP and Rolls-Royce. This studentship covers tuition, a tax-free stipend, funding
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Applications are invited for a PhD studentship in the Department of Computer Science at City, University of London. The successful candidate will work on developing a novel AI-powered conversational
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Start date: 29/09/2025 This is an exciting opportunity to study for a PhD funded by the EPSRC-funded EnerHy CDT and Sustainable Plastics Solutions. Offering an annual tax-free stipend of £20,780
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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providing a structured, semantic framework that enhances knowledge sharing and data reuse across different platforms and systems. Project Aim This PhD will develop an ontology-based methodology to improve