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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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energy transitions at local, national or global scales. Energy Engineering is a part of the Division of Energy Science in the Department of Engineering Science and Mathematics, which is a subject-wide
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PhD Position in Engineering Materials Project: Development and Characterization of Advanced Sorbents
). The division is part of the Department of Engineering Science and Mathematics. The department has several other research topics with activities that border on material technology, such as materials mechanics and
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emphasis will be devoted to practical problems in economics and finance, like the construction of high-dimensional optimal portfolios. Motivated by the widespread application of sample generalized inverses
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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) productivity, optimization and efficiency, and (4) implementation and use of innovative energy solutions. The PhD student position is part of the newly funded KKS Synergy project WorkFlex+ which focuses