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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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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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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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problems, recognise gaps in existing regulation and make use of signals from outside established institutions? Regulatory tools and processes: How can research access, public procurement, prototyping and AI
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knowledge of MR physics Experience with signal processing and/or image processing Experience with Linux systems and High Performance Computing Good oral and written presentation skills in Norwegian
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for the position. Preferred selection criteria Experience with machine learning and neural networks Basic knowledge of MR physics Experience with signal processing and/or image processing Experience with Linux
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to accurate sample reconstructions using advanced signal processing and tomographic reconstruction algorithms. With the inclusion of noise the object estimation accuracy will be based on statistical concepts
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largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing applications. As AI models continue to increase in size and computational complexity