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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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-loss events undermine statistical confidence. The aim is to develop i) edge intelligence (on-turbine smart algorithms for data preprocessing), ii) resilient data movement (error-tolerant, cybersecure
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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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to data from various sensors and radio signals? This is the main underlying theme to be explored within this postdoctoral position. The appointed researcher will investigate how AI embedded in physical