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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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of core web technologies. You have solid experience in Python and JavaScript programming languages. You preferably have experience with building and using machine learning models. You care deeply about
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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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the learning capabilities of feed-forward and recurrent models of neural circuits with various degrees of biological plausibility, with a focus on: Transferability of representations in multi-task settings
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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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machine learning models. You care deeply about privacy and are keen to create. You have a good command of spoken and written English. You are motivated to publish at top-tier academic venues. What we offer
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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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of semantics, pragmatics, philosophy of language, conversational analysis and dialogue modelling), the series of experiments will result in four journal papers, to be integrated into a dissertation. You will
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with rapid binary-population synthesis codes to detailed stellar evolution calculations with 1D stellar evolution codes. The models you develop will be directly linked to new and upcoming observations
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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