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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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: Equivalence checking of quantum circuits. This task will include the identification of suitable metrics for approximate equivalence and algorithms to efficiently compute approximation distances. A potential
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creative design processes. The lab will provide access to shared resources, joint supervision, and interdisciplinary training in AI, Life Cycle Assessment (LCA), and computational design tools. The objective
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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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machine learning algorithms, ideally with a focus on time-series data, anomaly detection, or edge computing (TinyML). IoT: You have a strong understanding of IoT communication protocols, data resilience
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Postdoctoral Position in Participatory Design of Autonomous Drone Systems and Human-AI Collaboration The Human-Centered Computing Group at Aalborg University (AAU) is seeking a talented postdoctoral
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systems, including integration of cyber-security. Enhance indoor climate by defining control strategies and developing control algorithms for demand-control ventilation, heating and cooling systems
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, computer science, and statistics The objective of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD
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Assistance in Complex Acoustic Environments within the general study programme Electrical and Electronic Engineering. The PhD Stipends are open from August 1, 2026, and the integrated PhD stipends are open for