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Fusion is a multiphysics environment, and their interdependency makes predictions extremely challenging. Components such as breeder blankets require nearly real-time simulations at the design and
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Science (LSE), is seeking a researcher to work on designing model ensembles that can efficiently explore the full range of plausible responses consistent with a greenhouse gas emissions scenario
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to transform our understanding and prediction of climate tipping points. We welcome candidates with expertise in climate modelling, ideally including experience with General Circulation Models (GCMs), Earth
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an outstanding Postdoctoral Research Scientist to undertake research isolating and understanding the most predictable components of the atmosphere and improving their representation in sub-seasonal prediction
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) ensembles by improving coastal hazard prediction in 5-7 days. SEA-COAST is funded by the Weather and Climate Science for Service Partnership Southeast Asia (WCSSP SEA) programme, managed by the UK Met Office
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Keywords: theoretical biophysics, machine learning, kinematics, (structural) biology. Context. Machine learning techniques have made significant progress in prediction of favourable structures from
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and scheduling for Department of Music, including production, teaching, and rehearsal scheduling. Coordinates applied music lesson and ensemble fees each semester using a multi-tiered and conditional
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ultra-high resolution atmospheric prediction models for better prediction, understanding, and projection of extreme weather events. The research topics include, but are not limited to: 1) predictability
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 8 days ago
of multiple timescales. Collectively induced stochastic resonance phenomena on molecular ensembles in optical cavities. Cavity-induced off-equilibrium consequences on chemical reaction rates Develop (ab-initio
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University of California, Los Angeles | Los Angeles, California | United States | about 21 hours ago
climate change projections.) These methodologies will be utilized to enhance the transparency and interpretability of predictive models dealing with complex climate data. Possible research areas include