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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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interdisciplinary research on knowledge extraction from social data. Project description The project is in the emerging area of fair social network analysis. In today’s algorithmically-infused society, data about our
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, signal processing and/or wireless communication. Basic knowledge of and/or experience in working with reinforcement learning/other machine learning algorithms Excellent command of spoken and written
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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: Intermediate Storage and Distribution for Maritime and Land Transport”, funded by Energimyndigheten. The project addresses key challenges in enabling large-scale compressed gaseous hydrogen infrastructure in
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absorption/fluorescence and scattering experiments at X-ray free electron lasers. Your focus will be to derive new algorithms for interpretation of the scattering data by introducing chemical force-fields via
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including modelling to determine the localization, distribution, and potential on/off-target effects of ONs in vivo. The final aim is to gain know-how on how to optimize formulations for different