579 postdoctoral-image-processing-in-computer-science PhD positions in United Kingdom
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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humans. The successful candidate will join the new Intelligent Robotics group in the Computer Science Department in the Computational Foundry in the Faculty of Science and Engineering at Swansea University
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Type of award Scholarship Managing department Faculty of Science and Engineering Value The four-year funded A*STAR PhD programme at Manchester enables postgraduate researchers in science and
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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 with: • Relevant subject matter experience at required level (e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) • Willingness to adapt and work across different
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(e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) Willingness to adapt and work across different disciplines Ability to work independently and cooperatively Commitment
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Research Infrastructure? No Offer Description Two fully-funded 3-year PhD studentships are available in Neuromorphic and Bio-inspired computing at the interface between control engineering, electrical
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use this formalisation to encode our STV algorithm on encrypted ballots. This approach aims to ensure both the correctness and privacy of the tallying process, paving the way for verifiable and secure
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Research Platform (SARRP) and in vivo imaging to develop image-guided radiotherapy (IGRT) strategies for liver and childhood brain cancers. A key focus of this project is hepatocellular carcinoma (HCC
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Systems, or a related field. Strong analytical and critical thinking skills. Strong machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor