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1st October 2026 Languages English English English The Department of Electronic Systems has a vacancy for a PhD Candidate in Machine Learning & Signal Processing for Industrial Applications Apply
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SINTEF, Equinor, and Total. The main objectives of the project include the development and the integration of signal processing and machine learning methodologies aiming to improve flow assurance via field
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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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-low-power CMOS integrated circuits and systems, in-memory computation, signal processing, telecommunications, and semiconductor materials. We particularly welcome applications from individuals from
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to designated sponsor or associate contractor and second party locations within and outside the continental United States. We are searching for analytical engineers with signal processing skills to join the
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knowledge of MATLAB/Python and signals processing Understanding of electromagnetics Genuine interest in battery technologies Experience with CAD and mechanical design How to apply: Interested candidates
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to designated sponsor or associate contractor and second party locations within and outside the continental United States. We are searching for analytical engineers with signal processing skills to join the
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computing; data science; signal processing; neuroengineering; bioinformatics; computational neuroscience. A PhD is not required. Candidates holding a PhD are also eligible, provided that their profile
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Integrated optics is currently experiencing unprecedented growth, driven largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing
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-efficient wideband signal processing and programmability to accommodate different use cases are becoming essential. Increasingly, overall system performance is no longer limited solely by the front-end, but