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diagnostic tools to support the managements of patients with stroke. This is a unique opportunity to work in a multi-disciplinary, collaborative environment at the interface of AI, machine learning
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We are looking to appoint a research scientist to carry out research in machine learning and artificial intelligence to develop interpretable clinical decision support tools and novel methodologies
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and esteemed industrial and governmental partners. Your expertise in machine learning, statistical analysis and programming will drive impactful research aimed at solving real-world challenges. Why join
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. This data will help shape paediatric-specific T2T endpoints and facilitate the development of personalized treatment strategies. You will apply advanced statistical and machine learning methods, and your
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and esteemed industrial and governmental partners. Your expertise in machine learning, statistical analysis and programming will drive impactful research aimed at solving real-world challenges. Why join
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to problem solve and work independently Desirable criteria Familiarity with the JASMIN data analysis facility Expertise in the hazard of extreme heat Competence in statistical analysis and/or machine learning
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. This data will help shape paediatric-specific T2T endpoints and facilitate the development of personalized treatment strategies. You will apply advanced statistical and machine learning methods, and your
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imaging brain function that uses the new technology of Optically Pumped Magnetometers (OPMs). You will primarily help develop and apply new machine learning methods for analysing data from the OPM-MEG
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their own niche of professional training and development. Examples of projects from the lab include identification of cancer drivers in individual patients using machine learning (Mourikis Nature Comms 2019
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of experts in machine learning and colour vision, including Dr Alexandros Koliousis (NU London), Professor Rhea T. Eskew (NU Boston), and Professor Andrew Stockman (UCL), as well as with technical