100 data-"https:"-"https:"-"https:"-"https:"-"UNIVERSITY-OF-LUXEMBOURG" positions at Aalborg University in Denmark
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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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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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) 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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candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a master’s degree in human-computer interaction, computer science, interaction design, applied
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University, preferably 3-6 months at a foreign research institution. Please visit the website of the doctoral school for further information on admission requirements. Who we are The research group focusses
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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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(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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register and survey data. The integration of migrants and questions of potential return migration are increasingly important social issues across Europe, including Denmark. As many first-generation
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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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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