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invite applications for a PhD student in the area of ?parameterizing ocean mixing?. The position is initially limited for three years. Equal opportunity is an important part of our personnel policy. We
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invite applications for a PhD student in the area of “parameterizing ocean mixing”. The position is initially limited for three years. Equal opportunity is an important part of our personnel policy. We
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address: Dr Fahad Panolan: f.panolan@leeds.ac.uk Project summary The Algorithms group at the University of Leeds (UK) is offering a fully funded 3.5-year PhD studentship on Parameterized Complexity and
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represent? Why do over-parameterized models trained with simple optimizers generalize so well? We explore these questions through the lenses of statistical learning theory, optimization theory, and
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develop, test, and implement new, physics/AI hybrid parameterizations of subgrid-scale processes in the Climate Modeling Alliance’s (CliMA’s) Earth system model. The focus will be on atmospheric processes
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implementation, testing and further development of new machine-learning parameterizations for subgrid atmospheric processes (convection and turbulence) and observations-based nudging tendencies in the Community
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insights for folding pathways and kinetics. There is an exciting opportunity to advance the state-of-the-art in this field, which would have important and wide-ranging impacts. Training. PhD thesis in
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have a PhD in computer science, mathematics, physics, or related fields, with a passion for programming. A desire to contribute to the development of open-source software within the context of the agreed
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100%, Zurich, fixed-term The Atmospheric Physics group at the Institute for Atmospheric and Climate Science (IAC), ETH Zurich invites applications for a PhD position (3 to 4 years) focused
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biodiversity. Specifically, the primary focus of the PhD will be to analyse and parameterize models describing the ecological and evolutionary dynamics of small and fragmented populations, and how the risk of