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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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integrated with the NiMARE (NMA) software project. To be considered you will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain
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will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain imaging data and possess sufficient specialist knowledge in brain
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Transactions on Probabilistic Machine Learning. A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, L Kennedy, J Gabry, PC Bürkner, M Modrák (2020). Bayesian Workflow. B Carpenter, A Gelman, MD
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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team, you will apply cutting-edge machine learning and deep learning techniques to dramatically reduce testing cycles. You will lead life cycle analyses, implement advanced health monitoring strategies
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Overview Nature offers a mechanism - called homeostasis - by which life forms can maintain their physical integrity and well being. On the other hand, a series of machines, including robots, cannot
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, artificial intelligence/machine learning, digital twins, and blockchain technology for operations and maintenance. This position is part of the RESTORE project, which aims to develop, test, and deploy
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, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful