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At the Technical Faculty of IT and Design of the Department of Sustainability and Planning, Copenhagen, a position as Postdoctoral researcher in Geospatial Machine Learning for Predicting Land Use
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The National Center of Excellence for Molecular Prediction of Inflammatory Bowel Disease (PREDICT), based at the Department of Clinical Medicine, Aalborg University in Copenhagen, is looking to recruit a talented researcher for a full-time 3-year postdoctoral position (37 hours per week) in...
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machine learning methods for detecting, classifying, and identifying wireless anomalies in real-world radio environments. You will design and experiment with AI-driven approaches for spectrum analysis, work
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machine learning models directly on these edge devices for real-time anomaly detection and identification. You will develop robust signal acquisition and processing pipelines, translate research-grade
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Do you want to be part of a young, dynamic research group working on designing the next generation of sustainable energy materials using computational chemistry and machine learning? And do you see
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the project based on your interests and in collaboration with a leading architectural firm. The candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a PhD
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or soon hereafter. The position is a 3-year Post Doc. The department was established in 1975. Today, we are located in two beautiful harbour-front locations in both Aalborg and Copenhagen. We have more
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in electrical engineering, computer engineering, computer science, or similar. Strong background in communication systems, optimization, or machine learning for networked systems. Experience and
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the Machine Learning and Artificial Intelligence. Solid mathematical and analytical skills. Knowledge about statistical machine learning, robotic perception, multimodal AI algorithms. Experience in programming
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: • Develop AI-driven control strategies for grid-forming inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation