123 data "https:" "https:" "https:" "https:" "UNIVERSITY OF LUXEMBOURG" positions at Aalborg University
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on development of wave energy and offshore wind. Most of our research is focused around work in our wave flume and basin. Further description of the group may be found here: https://vbn.aau.dk/en/organisations
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(such as heart disease, diabetes, and cancer) using, for example, data from registries and/or biobanks. The research will be performed in close collaboration with Center for Clinical Data Science (CLINDA
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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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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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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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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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(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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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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of student projects and participation in courses related to human-computer interaction and software engineering. Your competencies Applicants should have a strong interest in human-robot interaction and the