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and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge
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About us: We are seeking to appoint a postdoctoral research associate with an excellent track record in semantic technologies and machine learning. Topics of interest in this area include, but
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level. Successful candidates will teach and supervise students who are serving officers and civil servants in the UK and allied armed forces and partners. There are also opportunities to contribute
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Shrivenham and will undertake high-quality scholarship and support a range of professional military and security education courses at the postgraduate level. Successful candidates will teach and supervise
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, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research
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Robotics to develop research in the field, e.g., robot design, control and mechatronics; Publication record in robotics and machine learning, e.g., ICRA, IROS, RSS, CoRL, T-RO, CVPR, ICML; Excellent verbal
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contributing to multi-site or international collaborative research programmes, particularly in maternal, perinatal, or population health Experience applying machine learning or AI methods in healthcare research
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design, control and mechatronics; Publication record in robotics and machine learning, e.g., ICRA, IROS, RSS, CoRL, T-RO, CVPR, ICML; Excellent verbal and written communication skills, including academic
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supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning
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on quantitative phenotyping via generative modelling of quantitative MRI data. This exciting PhD position combines advanced machine learning with medical imaging physics to develop next-generation tools