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responsibility for carrying out research for understanding the learned algorithms in brains and machines. The post holder will provide guidance to less experienced members of the research group, including postdocs
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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging
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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging
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. Proficiency in Python and/or machine learning applications for data analysis. Ability to work independently and manage multiple research activities. Experience contributing to academic publications and
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understand this disease Travel to different medical centres as needed About you We're looking for someone with: A PhD (or nearly completed) in bioinformatics, computational biology, or similar field Experience
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We are seeking a highly talented and experienced Postdoctoral Researcher to join a research team led by Prof Chris Summerfield focussed on studying learning and decision-making in humans and machine
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, artificial intelligence/machine learning, digital twins, and blockchain technology for operations and maintenance. This position is part of the Maritime Future Fuels Training Plan project, which aims
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, artificial intelligence/machine learning, digital twins, and blockchain technology for operations and maintenance. This position is part of the Maritime Future Fuels Training Plan project, which aims
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engineering, or related disciplines who are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models
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execution. This work involves creating frameworks for adaptive decision-making, using techniques from operations research and machine learning. This particular thematic area will be supervised by Associate