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Contract type: Fixed term for 12 months Hours: Full-time About the role We are seeking a Full-Time Postdoctoral Researcher in Computer Vision CT image analysis to join the Nuffield Department of Surgical
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, or be close to completing, a PhD in statistical genomics, genetic epidemiology, data science, computing, artificial intelligence, biomedical engineering, or a related field. You will have significant
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to their design and characterisation. • Contribute to producing the relevant procedures and software tools in order to achieve the above. • Contribute to the design of relevant prototype components and participate
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to their design and characterisation. • Contribute to producing the relevant procedures and software tools in order to achieve the above. • Contribute to the design of relevant prototype components and participate
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strong technical expertise in deep learning, such as models for image segmentation, classification, multi-modal processing, foundation models, or agentic frameworks. An extensive background in computer
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, or be close to completing, a PhD in statistical genomics, genetic epidemiology, data science, computing, artificial intelligence, biomedical engineering, or a related field. You will have significant
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the future. The Institute brings together researchers in life and physical sciences, and engineering, to develop a spectrum of tools which we will use to image, interpret and intervene in biological systems
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for an additional 3 years (subject to the project progress). About You Candidates with a PhD degree in Electrical and Electronic Engineering, Biomedical Engineering, Physics or Material engineering are encouraged
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Qualifications This position requires a PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Biomedical Imaging, Computational Biology, or a closely related field. Research Record: A strong
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cross-cutting justification mechanisms — “national security” expansionism, “economic security” as a new paradigm, “strategic autonomy” and resilience, technology competition as existential framing