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Field
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working within Theme 3 of the Programme: ‘Image-guided Surgery’ and will involve the synthesis and assessment of novel multimodal nanomaterials for healthcare applications and radiolabel for PET imaging
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including the development, training, and testing of computer vision and machine learning tools for AI-automated anatomical landmark detection and segmentation of clinical images. Building upon previous work
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computer vision method for medical image analysis principally in oncology or pathology, with a possible focus on generative AI, explainability, multi-modality. Candidate’s profile A good Bachelors degree
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to demonstrate expertise in use, processing, manipulation and compression of raw camera data. Key duties for the role are to conduct in depth research into AI based automotive perception and relationship and
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in the future without them changing during observation. This project will use extensive mathematical processing of large sparse datasets, both simulated and experimental, to reconstruct image details
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imaging features to phenometabolic signatures from tissue samples taken during surgery and matched to the imaging. The project is part of the imaging theme for the new Nottingham Brain Tumour Research
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to phenometabolic signatures from tissue samples taken during surgery and matched to the imaging. The project is part of the imaging theme for the new Nottingham Brain Tumour Research Centre of Excellence. This is a
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About the role We are seeking an outstanding candidate to work in the Process Dynamics group to contribute to advanced research in AI-driven X-ray imaging for metal alloy solidification
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& Medicine. Department: PET Imaging Centre Facility. Contact details:John Joemon. joemon.john@nhs.net Location: St Thomas Hospital. Category: Professional & Support Services. About Us We are looking
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, machine learning, multiscale and multiphysics simulation, computational anatomy, medical image analysis, and integration of wearables and biosignal processing, applied to conditions ranging from cardiac