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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
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About us: The applicant will join the Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will
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-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will benefit from the extensive and broad expertise in AI and
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engineering, machine learning, molecular design, and sustainability, helping to create smarter ways of identifying promising sorbents for electrochemical CO2 capture. Over the course of the project
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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
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considered for Research Assistant. Strong programming expertise in Python and C++, with experience developing real-time robotic and AI systems. Experience in deep learning and computer vision, including
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publications or conference presentations (either as first-author or as a co-author) Machine learning and/or computational modelling experience Experience with brain network modelling and analysis Experience
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venues including Serpentine Arts Technologies, Southbank Centre, Barbican Immersive and more, you’ll develop cutting-edge research skills alongside practical expertise in machine learning, extended reality
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, and human-centred computing. You will join the Vision & Human-Robot Interaction (VHR) Lab, a multidisciplinary research group working at the intersection of robotics, machine learning, and human