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, moisture‑related defects and narrow processing windows, limiting their wider adoption. This PhD will address these challenges through a combination of experimental materials science, advanced
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and brain. Perform molecular, cellular and histological experiments, including AAV injections, tissue processing, immunostaining and stereological confocal image analysis. Develop and apply image and
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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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applications in aerospace, rail, automotive and battery technologies. However, current PFA systems suffer from brittleness, moisture‑related defects and narrow processing windows, limiting their wider adoption
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. The project will then consider polymer melts up to 200 °C, relevant for industrial extrusion. Working with industrial and academic partners, you will help establish a new materials‑processing paradigm with
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size, weight, power and cost constraints, accurate relative positioning and motion knowledge across platforms, coordinated data acquisition strategies, and the development of SAR image formation
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an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject Area Medical imaging, biomedical engineering, computer science & IT
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, including Machine Learning & Artificial Intelligence, Colour & Imaging, Computer Vision, Graphics, Data Science, Health Computing, Computational Biology, Cyber Intelligence and Networks. We collaborate with
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technologies for clays rely on high-temperature roasting followed by aggressive acid leaching, processes that are energy-intensive, generate substantial chemical waste, and produce significant carbon emissions
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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