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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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, this PhD thesis will focus on the characterization of multipolar electrograms (EGM) through graph signal processing (GSP). The underlying hypothesis is that local propagation patterns in AF are associated
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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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available at the Graduate School’s website: https://healthsciences.ku.dk/phd/guidelines/ Application procedure Your application must be submitted electronically by clicking ‘Apply for position’ below
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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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information about the dielectric properties of the surface and can therefore be used to infer changes in soil moisture. A major focus of the PhD will be to develop, test and improve robust GNSS-IR processing
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skills, to undertake a PhD in the Faculty of Arts are available at https://arts.monash.edu/graduate-research/application-process/ . Applicants should ensure they familiarise themselves with