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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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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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-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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, neuroimaging, neurophysiology, proteomics, transcriptomics, epigenomics, metabolomics, bioinformatics, cell models and animal models. First in man and Phase 2, 3 and 4 clinical trials are also strongly supported
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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, neuroimaging, neurophysiology, proteomics, transcriptomics, epigenomics, metabolomics, bioinformatics, cell models and animal models. First in man and Phase 2, 3 and 4 clinical trials are also strongly supported
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, neuroimaging, neurophysiology, proteomics, transcriptomics, epigenomics, metabolomics, bioinformatics, cell models and animal models. First in man and Phase 2, 3 and 4 clinical trials are also strongly supported
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be found in the Job Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Further
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. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Further Information We pride ourselves on being inclusive and welcoming. We embrace diversity and
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at the bottom of the next page after you click “Apply Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Further information: We ask all