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Applications are invited from PhD studentship candidates with good first degrees in computer science, physics, maths, biology, neuroscience, engineering or other relevant disciplines to join
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as early indicators of anthropogenic and climate-driven change. However, limited understanding of the processes shaping species’ biogeographic distributions constrains our ability to predict ecological
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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
developed a dataset by conducting high-velocity impact experiments on CFRP specimens using controlled testing setups. The multimodal dataset is to be processed using X-ray CT scans, SEM imaging, and
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, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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Discipline: Engineering & Technology, Materials Science, Mechanical Engineering Qualification: Doctor of Philosophy in Engineering (PhD) This project is a collaborative research effort between
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and toolsets for engineering measurements relevant to clinical settings. The project will be supervised by experts in DIC (Hari Arora), surgery (Iain Whitaker) and wider biomaterials imaging research
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data