565 postdoctoral-image-processing-in-computer-science-"UCL" PhD positions in United Kingdom
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. dos Santos is an Assistant Professor (Lecturer) in Computer Vision at the University of Sheffield. His research interests include remote sensing image processing, computer vision and machine learning
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and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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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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with young adult participants and/or their parents in each country, deliver the school-based body image programme (including cultural adaptation where necessary), and conduct quantitative and qualitative
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for Postdoctoral Researchers/Research Fellows in the following areas: Areas of interest: Privacy and Compliance, User Experience; Computational Data Science and Applications; High-performance, Energy-efficient
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need, with direct routes to translation and impact. You’ll have access to world-class computational facilities, real-world datasets, expert supervision across engineering and clinical science, and the
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by
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: Candidates should hold a UK (or international equivalent) first or upper-second Bachelor’s degree. Candidates with backgrounds in electrical and electronic engineering, physics, computer science and
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considered. Qualifications/Skills PhD degree in a programme relevant to human-computer interaction and/or critical computing, ideally in Computer Science, Industrial Engineering, Interaction Design, or a
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VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and