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these effects both require very high resolution and long time series of data, making it computationally expensive. By leveraging findings from recent km-scale modeling and exploiting high-resolution idealized
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analysis, as well as for data processing, integration, and interpretation. Current research directions include, for example, applying DIA-based strategies in large-scale studies, combining electron- and
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challenges. The work is conducted at the interface of mechanics, artificial intelligence, and computational science. The developed methods will be validated on benchmark problems and real-world data and
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deployment by enabling quick data collection, calibration, and policy training while ensuring safety and efficiency. For this, we develop novel learning-based control and policy optimization techniques. We're
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will not be considered. For more information on the Graduate Institute and the Department of International Law , please consult our websites. The Institute is an equal opportunity employer and values
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plants and investigating the impacts on the market/security. For this purpose, we will use data sourced from the ENTSO-E transparency platform and processed at the RRE. This upgrade will be utilized
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further involves supporting the generation of high-quality, reproducible data suitable for intellectual property (IP) development, regulatory pathways and potential commercial use. The technician will work
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address foreign supply shocks for strategic technologies, for instance energy technologies To this end, the doctoral student will conduct empirical studies with patents and other innovation data You will
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80%-100%, Zurich, fixed-term The Swiss National Supercomputing Centre (CSCS) develops and operates a high-performance computing and data research infrastructure that supports world-class science in
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compromise grid reliability and energy security. We proceed in two steps. First, we use AI-based document analysis and engineering data to construct detailed bills of materials (BOMs) for selected critical