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to the development of state-of-the-art nuclear-reaction models and evaluated nuclear-data libraries, supporting safe, reliable, and competitive technologies for both existing and future nuclear-energy systems, as
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Large dependencies of reliable power production from offshore renewable energy systems (RES) is expected in the next decades, in particular onshore and offshore wind and solar PV. Large changes are also
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within the accelerator field, including accelerator physicists, high –frequency structure and magnet experts, and laser experts. The Accelerator Development team is a part of MAX IV Accelerator Division
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science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and
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must be inferred from the data. The overall goal is to develop reliable and robust statistical methods that can contribute to scientific understanding and inform decision-making and public policy
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, calibration and reliability of large pre-trained models Probabilistic generative models and world models Probabilistic machine learning for scientific discovery Don’t see your exact idea listed? We encourage
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and statistical methods as part of a close collaboration between Uppsala University, Westinghouse, and Vattenfall? Would you like to contribute to the development of fast, robust and reliable
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-tolerant composite structures faster, smarter, and more reliable. As a team, we will develop a computational framework that links small-scale material defects to large-scale structural performance, enabling
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understand why species and populations differ in their vulnerability, so that research can inform conservation, management, and policy. However, we still cannot reliably predict how climate change will affect
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, and policy. However, we still cannot reliably predict how climate change will affect animal populations across their full life cycle. Accumulating evidence suggests that early life stages can be more