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. Project description This PhD project focuses on advancing the scientific computing foundations of quantum spin dynamics by developing efficient numerical algorithms for modeling complex, open quantum
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background, the teaching may also be in other aspects of software development (DevOps, Algorithms etc.) or informatics (e.g., content design, user experience design and human-computer interaction). You are
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execution of experiments, and discuss development of eg. user sample environments or analysis code for nanoprobe experiments As a scientist, you are ready to perform scientific research or nanoprobe method(s
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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Safe and efficient ice navigation supported by satellite data Join us at the Division of Geoscience and Remote Sensing and help advance knowledge about sea ice dynamics and develop the capability
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Do you want to contribute to groundbreaking research in the development of a theoretical framework and numerical algorithms for evolving stochastic manifolds? This is an exciting opportunity for a
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reconstruction, and the need to evaluate generated and transmitted data in terms of their relevance and utility for achieving specific objectives. To address these challenges, the project will develop theoretical
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develop and analyze mathematical models and algorithms that connect partial (and/or stochastic) differential equations, infinite-dimensional optimization, and statistical machine learning. The goal is to
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the development of stochastic models for decentralized energy markets, decentralized and learning-enhanced market clearing algorithms, and fair-by-design pricing strategies. The research will address one or more of
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research on the development of new inference methods and algorithms for wide classes of stochastic models. However, research will be conducted in collaboration with biologically oriented researches allowing