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prediction to process optimization. The focus of this PhD project is to develop and apply machine learning methods across three interconnected tasks: 3D microstructure characterisation. The student will
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for hypergraphs and partially ordered sets (POSets), funded by the Swedish Research Council. This project is concerned with saturation problems for two classes of combinatorial objects: hypergraphs and posets
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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, such as heterogeneity of data sources and communication constraints. By leveraging tools from statistical signal processing, machine learning, optimization, and mathematical modeling, the project aims
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algorithms. Our research integrates expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems
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dynamics. Particular emphasis is placed on opinion dynamics as well as distributed problems in coordination, optimization, and learning. The research encompasses both theoretical and computational aspects
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of Clinical Sciences Lund is one of six departments at the Faculty of Medicine. Clinical Sciences Lund cooperates closely with Skåne University Hospital and the Faculty of Medicine in order to optimize
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Sciences Lund cooperates closely with Skåne University Hospital and the Faculty of Medicine in order to optimize the conditions for preclinical and clinical translational research, research strategies and
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at the Faculty of Medicine. Clinical Sciences Lund cooperates closely with Skåne University Hospital and the Faculty of Medicine in order to optimize the conditions for preclinical and clinical translational
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involve the conceptual and practical development of the methodology for electrochemically initiated time-resolved soft X-ray spectroscopy, including construction and optimization of measurement setups and