137 data "https:" "https:" "https:" "https:" "University of Aberdeen" positions at Aalborg University
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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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(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
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testing and condition monitoring using modern machine learning, including multimodal foundation models and related data-driven and physics-informed approaches. Research topics may include visual and real
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(LLMs) to explore historical text data and cultural heritage collections. Collections of historical texts are increasingly used to train AI, but, consisting of highly heterogeneous text data
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, mathematical engineering, acoustics, machine learning or similar; Solid mathematical and analytical skills, including signal processing, optimization, machine learning or information theory; Experience in
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macroeconomic paradigms. The research will include: Macroeconomic modelling (using SFC and other approaches) Macroeconomic theory covering different paradigms in macroeconomics Integration of financial data
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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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disturbances or cyberattacks, such as sensor manipulation, electromagnetic interference, or injected faults, can affect the behaviour of power electronic systems. Developing data-driven models that capture how