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Field
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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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spectrum of topics in CNU sections 27 "Computer Science" and 61 "Computer Engineering, Automation and Signal Processing". The laboratory is located at the heart of the Sophia Antipolis technology park, in a
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modern machine learning, statistical signal processing, or optimisation to turn heterogeneous knowledge (channel/network state, maps and topology, mobility, hardware constraints, and task-level KPIs
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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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Development Personnel regarding support staff in research and development activities. Specific Requirements Neural data analysis. Signal processing. Optimization and support for signal acquisition in laboratory
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approaches for multi-frequency and multi-constellation observations. This may include signal selection and quality control, low-elevation satellite arc processing, spectral analysis, reflector-height
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deposition characteristics from discharge signal data. The aim is to reduce process development iterations for EDM shaping with concurrent functionalization of surfaces by deposition of elements from electrode
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Building a quantum computer that can solve real-world problems will require the integration of many highly coherent qubits. Hole-spin qubits in planar germanium quantum wells are among the most
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or equivalent tools will be used for signal processing, system identification and quantitative comparison between electrical measurements and independently measured reference data. The project will therefore