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the next generation of PV technologies for beyond 2030. The new postdoctoral research position will use materials modelling techniques (DFT, molecular dynamics, machine learning potentials) to investigate
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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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they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (e.g. Statistics, Machine Learning, Biostatistics, AI
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, data normalisation and machine learning methods applied to biological datasets Experience with data management and version control (Git/GitHub, workflow automation, documentation) Capacity to work
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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models
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the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics, Statistical Machine Learning, Deep Generative Modelling, or a closely related field, together with relevant
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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
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difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (eg Operations Research, Management Science, Statistics, Machine Learning, Applied Mathematics
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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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to conduct multidisciplinary research around robot learning for autonomous robotic chemists, with a background of excellent research outputs across Robotics and Machine Learning, ideally with a background in