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contribute to high-impact research on machine learning related to the analysis of IoT data in the form of multivariate time series. The DESS group is part of Department of Computer Science that belongs
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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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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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collaboration with a leading architectural firm. The candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a PhD degree in human-computer interaction, computer
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intelligence within grid-connected power converters and variable-frequency motor drives with edge computing and machine learning capabilities. We offer a multidisciplinary, international, and friendly atmosphere