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public procurement. This research addresses a broad set of topics including optimal taxation and public expenditure, income formation, household responses to taxation and other economic policies, social
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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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multiagent dynamics, with special focus on human decisions and opinion dynamics. The research will deal with both theoretical and computational aspects. The student will develop dynamical models and apply them
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description The subject of Energy and Environmental Engineering is built up and developed by the research in the research specialisation of Future Energy. This research programme is mainly technologically
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and development centre – an excellent infrastructure to develop and optimize membrane processes from lab to pilot scale. The project is part of COMPEL. COMPEL, "COMPetence for the ELectrification
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landscape, the focus of this position is on process design, system integration, and optimization of performance. Teaching at first, second and third cycle level is a central part of the department's mission
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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and activities connected to our PhD program. In addition to producing individual research, the applicant is also expected to interact with existing researchers within the department, and to contribute
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artificial intelligence), exploring future skills, and optimizing equipment management. You will work in close collaboration with major industry partners to collect and analyze real-world empirical data using