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physics, computational astronomy and an unprecedented amount of data driven by observation. You will learn to run simulations on high-performance computing clusters, ranging from broad parameter studies
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addresses this challenge in two ways: We investigate the fundamental neural mechanisms that control movement. We explore engineering-based solutions to restore function when these pathways are disrupted. As a
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candidate, you will investigate the learning capabilities of feed-forward and recurrent models of neural circuits with various degrees of biological plausibility, with a focus on: Transferability of
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lead to debilitating motor disorders. Our research addresses this challenge in two ways: We investigate the fundamental neural mechanisms that control movement. We explore engineering-based solutions
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of data driven by observation. You will learn to run simulations on high-performance computing clusters, ranging from broad parameter studies with rapid binary-population synthesis codes to detailed stellar
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, engineering physics or mathematics. You have a good command of analytical techniques used in the modelling of complex systems, and of statistical mechanics methods (particularly as used in the physics of spin
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training programme on Privacy for Smart Speech Technology(link is external) (PSST), which is funded by the Horizon Europe Marie Skłodowska-Curie Action. You will receive a joint doctorate from Radboud
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key physical properties of mixtures of molecules, including solubility, viscosity, and surface or interfacial tension. We will train a range of AI models to allow us to predict these properties from
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, viscosity, and surface or interfacial tension. We will train a range of AI models to allow us to predict these properties from the chemical structure alone. Once established, we will expand the self-driving
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the other SPINES PhD projects on (a) ‘Infrastructure Managers as Institutional Entrepreneurs’ (University of Groningen), and (b) ‘Modelling Shared Pathways and Tipping Dynamics’ (University of Twente