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specifically, the PhD student will examine dynamics of sensory processing with a particular focus on the suppression of sensory input around movement initiation. Projects will involve using physiological
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questions include what compliance means formally when no party sees the whole picture, how enforcement can be verifiable rather than trusted, and what these guarantees cost. The work spans cryptography
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to image the centre of live, intact, plant roots. The ability to observe dynamic cellular processes at the centre of a live root for the first time will unlock entirely new lines of biological inquiry
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) to establish the thermal behavior of batteries under simulated abusive conditions, alongside advanced materials characterisation tools (including electron and X-ray imaging). Collectively, these tools will
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through the application of advanced imaging tools, including X-ray tomography. Eligibility This studentship is funded by The Dept of Engineering Science and is associated with the Faraday Institution LiStAr
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evolution at high temperature. The transition towards smarter, lower-carbon manufacturing demands new ways to understand and monitor how materials evolve during processing. This PhD project addresses a
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patients. Existing assistive technologies rely heavily on digital image processing or bulky external devices, which can be expensive, inconvenient, and inaccessible – where simple prescription lenses simply
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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research on nanoscale control of optical fields for applications in optical imaging and photonic chip technology. The research will be focused on the design, fabrication, and testing of optical components
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several benefits, including thermal conductivity, electrical insulating and creating the necessary structural integrity needed around the battery. However, this process can be slow, induces an element of