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, providing direct translational relevance. By combining state-of-the-art imaging with molecular and in vivo approaches, this project offers unique training in both mechanistic science and applied cancer
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, computational biology, or related disciplines (or equivalent experience), combined with extensive experience in processing and analysis of imaging data, evidenced by a publication record and portfolio of projects
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/Directorate: School of Medical Sciences This is an outstanding opportunity for a Research Associate, with a background in deep learning and medical image analysis, to work within the reirradiation research team
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activities. The post holder will be appointed in the Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences (BMEIS), where their duties will include academic, clinical
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and teaching portfolio in AI, with a focus in data science, machine learning, image analysis, natural language processing (NLP), Large Language Models (LLMs) or generative AI. You will contribute
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develop the XNAT open-source imaging informatics platform. The ideal candidate should also have experience developing scientific documentation. A job description and person specification can be accessed
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Sciences (LMS) in the Computational Cardiac Imaging Group headed by Professor Declan O’Regan. The LMS is a world-class research laboratory where scientists and clinicians collaborate to advance
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of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences (BMEIS), where their duties will include academic, clinical and teaching work. BMEIS is a cutting-edge research and teaching
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-researcher whose work and teaching engage the relationship between text & image, broadly understood. The postholder will contribute 0.4 FTE to the MA Photography programme and 0.4 FTE to the MFA Arts
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Full-time: 35 hours per week Fixed-term: 13 months The opportunity: Conduct original research on neuronal networks underlying the processing of natural visual stimuli, using in vivo large-scale two