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the interfacial strength, nano-scale 3D structure and residual stresses in advanced power electronic materials (INTERVENE), and is fixed-term of 18 months. Power electronics is a major technology sector for the UK
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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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PhD/DPhil in Computer Vision or Machine Learning (or be near completion) and hold a strong publication record in this field. You must have sufficient theoretical and practical knowledge of methodologies
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interface of materials science, cell biology, pharmacology and medicine in collaboration with Dr Craig Lygate (University of Glasgow). This project aims to develop and optimise targeted graphene-based
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to less experienced members of the research group, including postdocs, research assistants, technicians, and PhD and project students. In this post you will manage your own academic research and
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group with responsibility for carrying out research on the spin-resolved electronic structures of quantum materials, such as topological quantum materials and unconventional magnetic systems, making use
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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work. About you Applicants should hold a PhD/DPhil, or be near completion of a PhD/DPhil in structural biology, biochemistry or related area and have gained experience in a wide range of structural