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Engineering field in computer science, or related field. Strong expertise in natural language processing (NLP) and large language models (LLM) Over 1-year research experience in the above required areas
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proposal writing Ph.D. in Computer Science, Engineering, Biology, or a related field with a focus on machine learning or computer vision Minimum 5 years in multimodal image analysis OR deep learning
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to the clinic The post holder will be based in the Department of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers
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of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers designing and translating technology into the clinical
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, if applicable. Assist radiologist with interventional Nuclear Medicine procedures. Evaluate Nuclear Medicine scans for technical quality, collate processed images in sequence of exposure and appropriately label
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proper archiving protocols for processing and storing all acquired images related to procedures. Maintain patient confidentially and demonstrate exemplary customer service skills. Performs Quality Control
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instruments (e.g. Thermo Orbitrap technology). Experience in using (AP-)MALDI technique for analysis and imaging. Experience in LC/MS for targeted or untargeted studies is an asset Ability to execute research
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to groundbreaking imaging techniques alongside world-class physicians and cutting-edge technology. At MU Health Care, your passion for patient care and technical excellence makes a real impact. If you're energized by
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, hotels and more · See a comprehensive list of benefits here . DETAILED JOB DESCRIPTION Perform complex tasks associated with the operation of advanced imaging protocols such as CT Colonography, CT
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Klenerman in the Yusuf Hamied Department of Chemistry, from October 2025 for up to 2 years. This is a collaborative project with Professor Clare Bryant in Clinical medicine and aims to image and characterise