104 data-"https:"-"https:"-"https:"-"https:"-"ASNR" positions at Aalborg University in Denmark
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Communication, the Faculty of Social Sciences and Humanities and the Center for Clinical Data Science (CLINDA), Department of Clinical Medicine, the Faculty of Medicine. AI:GENE-XPLAIN develops AI tools
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experimental methods such as viromics and metatranscriptomics. The data will be linked to soil and emission data to help create predictive models. Within a broader framework, your work will contribute
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) Data-driven and AI-assisted methods for power electronics Across the above areas, you are expected to contribute to model-based and data-driven/AI-based methods, including digital twins, physics-informed
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, the spatial and temporal resolution of EO data. MASSIV-EO aims to overcome these limitations through foundational research on architectures and methods for the real-time delivery of EO data from dense
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optimization of production systems and supply chains, including digital twins, virtual system validation, process modeling, and data-integrated decision models. Research should explicitly support managerial
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using signal changes to learn about the weather and take appropriate action. By combining AI with physics and real-time data, the project improves weather forecasts and makes communication systems more
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-drive systems. Across the above areas, you are expected to contribute to model-based and data-driven/AI-based methods, including digital twins, physics-informed learning, data analytics, and AI-assisted
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(students, staff, and visiting researchers) with sample preparation, measurements, and data analysis Participation in maintaining laboratory safety, including handling of equipment and chemicals Teaching
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more about the department at www.es.aau.dk. Your work tasks The PhD project is part of a bigger Novo Nordisk Foundation (NNF) New Exploratory Research and Discovery grant entitled: Information Theoretic
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of wind turbines. Despite remarkable progress in structural health monitoring boosted by AI, purely data-driven models have no physical interpretability and poor generalization capabilities. Thus