685 phd-position-for-fully-funded-reserch-in-computer-vision Postdoctoral positions in United Kingdom
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We are seeking a full-time Postdoctoral Research Assistant in Computer Vision to join the Visual Geometry Group (Central Oxford). The post is funded by ERC and is fixed-term for 1.5 years with a
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mathematical and computational techniques, it is essential to have experience in mathematical modelling / dynamical systems theory / numerical methods / coding. An ideal candidate would have a PhD, or
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vision research. The department fosters interdisciplinary collaboration, addressing real-world challenges through innovative machine learning, data science, and intelligent systems research. About the role
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at the Department of Engineering Science (central Oxford). The post is funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer
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funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
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patients with hearing disorders. You will join a collaborative environment where your technical expertise in computer vision will contribute to clinical applications. Our team are now expanding our work
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Applications are invited for a fully funded fixed-term at the Research Assistant / Associate (PostDoc) level in high performance computing for computational fluid dynamics applications. High
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Location: South Kensington campus, hybrid working About the role: Applications are invited for a fully funded fixed-term at the Research Assistant / Associate (PostDoc) level in high performance
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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
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Postdoctoral Research Associate: An exploration of the relationship between funding and medal targets, and athlete experience. ( Job Number: 25000663) Department of Sport & Exercise Science Grade 7