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Job Description Are you interested in working at the intersection of optimal control, AI algorithms, and game theory, on problems that matter for real-world critical infrastructure? This PhD
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, international group of 13 researchers from 8 countries, with expertise across energy systems and markets, optimization, control, game theory, and machine learning. Interdisciplinary by design: Work at the
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, mathematical optimization, laser physics, integrated photonics, condensed matter physics, and spectroscopy. If you are passionate about advancing nanophotonics through cutting-edge research, we warmly encourage
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/ TensorFlow / Scikit Learn Highly knowledgeable in mathematical and statistical concepts Solid foundation in mathematics for Machine Learning (Linear Algebra, Probability, Optimization). Proficient in English
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green transition. Due to the complexity and heterogeneity of the biological mechanisms underlying fermentation, achieving optimal performance often requires fine-grained, time-dependent, control
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. Responsibilities and qualification Molecular thermodynamics plays a crucial role in the modelling, design, and optimization of various systems in product and process engineering. Despite significant progress made
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in the group of Niels Engholm Henriksen (https://www.kemi.dtu.dk/english/research/physical-chemistry ). You must have a solid foundation and interests in quantum chemistry, applied mathematics
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implementation of these within optimized computer code, but also large-scale applications of the resulting methods to various chemical problems of interest. Candidates with a strong background in theoretical and
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in computer science or applied mathematics and a strong interest in electrochemistry, molecular modeling, and sustainable energy technologies. Experience with computational methods, data analysis
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engineering, or similar. Solid mathematical and analytical skills, including signal processing and optimization. Knowledge about classical and/or quantum data communication, including for instance error