14 parallel-processing-bioinformatics-"Multiple" Fellowship positions at King's College London
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Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of Electronic Health Records from people with epilepsy across multiple NHS
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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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experience: Essential criteria PhD awarded in genetic epidemiology, statistical genetics, bioinformatics or related discipline Postdoctoral research experience in genetic epidemiology, statistical genetics
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future development of an ongoing epilepsy research project funded by the UK Epilepsy Research Institute. The Research Fellow will be using Natural Language Processing (NLP) methods, with a special focus on
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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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multiple fields and audiences. This is a full time post (35 Hours per week), and you will be offered an a fixed term contract until 31 August 2028. About you Please note that these are development positions
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to equality, diversity, and inclusion, actively addressing areas of potential bias Desirable criteria Experience of working with multiple nations on global health Evidence of building research capacity in LMICs
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of the recruitment process. We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community. We are committed
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’ NHS Foundation Trust and the Department of Twin Research at King’s College London. The fellow will be supervised by Consultant Geriatricians/Physicians throughout this process. This is a part time post
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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 pride ourselves on being