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into four research thrusts that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics The objective
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engineering, acoustics, machine learning or similar; Solid mathematical and analytical skills, including signal processing, optimization, machine learning or information theory; Experience in programming, e.g
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computing technologies. The group has a long tradition of empirical and solution-oriented research focusing on processes, products, and theory. The PhD fellow will join the Human Augmentation and
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academic background with a master’s degree or equivalent in Energy Engineering, Electrical Engineering, Mathematics, Control theory, or any other related discipline, potentially with skills in Power
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degree or equivalent in Energy Engineering, Electrical Engineering, Mathematics, Control theory, or any other related discipline, potentially with skills in Power Electronics Converters and Control
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volatility. CLASSIQUE is organized into four research thrusts that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and
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, conducting theory-driven statistical analyses of longitudinal register data, and, where relevant, linking these with existing survey data. The PhD student will contribute to international journal publications