489 parallel-processing-bioinformatics positions at KINGS COLLEGE LONDON in United Kingdom
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-quality teaching. The Hub for Applied Bioinformatics (HAB) is the Faculty’s focal point for computational biology, delivering bespoke bioinformatics support and training across genomics, transcriptomics
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the Faculty of Life Sciences & Medicine Hub for Applied Bioinformatics. This post is jointly funded by the Borne Foundation (50%) and King’s Health Partner’s Centre for Translational Medicine (CTM) (50
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backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate closely with experimental scientists and contribute
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Treatment. The post-holder will work in the School of Biomedical Engineering & Imaging Sciences, King’s College London, with a team of investigators covering AI, computer vision, robotics, and medical imaging
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that combine deep learning, computer vision, and bioinformatics to extract actionable insights from complex, multi-modal data, including medical imaging, genomics, and clinical records. A central theme of our
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the Medical Research Council. The Research Fellow will be using Natural Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of
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infectious diseases and population health), close ties with NHS partners, and a commitment to translational research and high-quality teaching. The Hub for Applied Bioinformatics (HAB) is the Faculty’s focal
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to develop novel immune therapeutic strategies for hard-to-treat triple negative breast cancers (TNBC). Based in the Cancer Bioinformatics Group (Professor Anita Grigoriadis), the postholder will contribute
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and clinicians at King’s and the Institute of Cancer Research to develop novel immune therapeutic strategies for hard-to-treat triple negative breast cancers (TNBC). Based in the Cancer Bioinformatics
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. The focus will be on a stage of disease when both confirmation of the diagnosis and measurement of therapeutic response remain challenging. You will be specifically involved in two parallel studies making use