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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 closed-loop brain–computer interfaces aimed at restoring motor function in models of motor disorder. Some part of the role may involve teaching and up to 0.1 FTE of your time may entail teaching activities
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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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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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at restoring motor function in models of motor disorder. Some part of the role may involve teaching and up to 0.1 FTE of your time may entail teaching activities. A fully funded PhD position is available
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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
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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 participate in relevant conferences
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evolution calculations with 1D stellar evolution codes. The models you develop will be directly linked to new and upcoming observations, including the just-released 4th gravitational-wave observations (O4