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scientific numerical codes, compilers, code optimization, file input/output strategies, and data management. Experience using data analysis and machine learning libraries. Excellent knowledge of computing
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(e.g. sparse-view and/or high-noise) data. Develop and validate numerical implementations on simulated and real CT data. Explore and compare supervised and self-supervised machine learning/AI-based
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Python, and familiarity with relevant machine learning frameworks. A solid understanding of mathematical modeling, optimization, or numerical methods. Experience in one or more of the following areas is
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machine learning Experience in optimization and message-passing algorithms Previous experience in research, publication, and teaching Swedish language skills are not required for this position. If you are
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following points: Machine learning techniques, statistics, and probabilities Numerical methods for time-domain simulations Power system dynamics Power system optimization Programming tools such as Python
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international team combines materials chemistry, optical spectroscopy, electron microscopy, theoretical modeling, and numerical simulation to understand and control materials at the nanoscale. Project background