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Solution project " ASMADI - AI based Spectrum Monitoring for Anomaly Detection and Identification" to develop signal processing algorithms that enable autonomous detection, classification, and filtering
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closely with signal processing pipelines built on real measurement data — including baseband I/Q signals — and contribute to both algorithm development and experimental validation. The role involves close
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algorithms into efficient edge inference systems, and validate end-to-end performance under real-world deployment conditions. Throughout, you will work with live measurement data spanning the full arc from
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. The objective is to develop models and algorithms that capture spatial variability, uncertainty, and communication constraints, and to understand how these factors influence perception, adaptation, and
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algorithms. This work will be evaluated through simulations and with physical drones in mock search-and-rescue missions. This position will involve close collaboration with the PhD student at SDU who is
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. The candidate will design models and algorithms for learning and decision-making under uncertainty, optimized for real-time operation on heterogeneous physical devices. Finally, the position will address how
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++) Knowledge of the fundamentals of ML/AI algorithms for communications and networking, and their implementation A creative mindset and curiosity to research and develop new solutions with highly skilled