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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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more sensitive and faster cancer imaging. This PhD project will focus on surface functionalisation of metascintillators to optimise their scintillation performance, light yield, timing resolution, and
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Families, and sponsors of International Women in Engineering Day. We are also Disability Confident Level 1 Employers and members of the Business Disability Forum and Stonewall University Champions Programme
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apparatus equipped with thermocouples and thermal imaging to simulate realistic runaway events. Top-performing coatings will be validated in situ on live EV cells under controlled runaway conditions. Dr
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in a related discipline. This project would suit motivated graduates from a wide range of STEM backgrounds—including environmental, civil, chemical or mechanical engineering, computer science, robotics
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
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of their machines is maximised, or machine downtime is minimised. The aim is to develop a smart sensor prototype and demonstrator for condition monitoring of low-speed bearings. The following objectives are defined
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the growing demand for sustainable AI-enabled systems, this PhD brings together low-power computing, energy-aware design, and thermal optimisation. You’ll work with advanced profiling tools, prototype long-life