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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine learning for improving
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engineering Chemistry Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 10 May 2026 - 23:59 (Europe/Brussels) Country Belgium Type of
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will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato, other members of the Cambridge Machine Learning Group (mlg.eng.cam.ac.uk ) and
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, aiming at improving the information extraction and the of icy planetary bodies subsurface by radar sounder data processing. The selected candidate will be expected to develop novel machine learning methods
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An exciting opportunity is available for a motivated and talented PhD candidate to develop a transformative technology for managing the UK’s nuclear graphite waste. Funded by the Nuclear
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AI hardware beyond traditional computing architectures. Gain a unique combination of skills in mathematics, machine learning, and photonics. Be part of a multidisciplinary research team spanning
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diplomas. Qualifications and specific competences Applicants must hold a relevant master’s degree (120 ECTS) in Electrical Engineering, Computer Science, Machine Learning, Artificial Intelligence
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integration, algorithm development and the creation of machine learning tools required for the project’. The successful candidate must have advanced knowledge of computer engineering, particularly of artificial
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is linked to the ELLIIT project New Machine-Learning Methods for High-Dimensional, Population-Scale Health Data , conducted in collaboration with Lund University. The project aims to develop and apply
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University of Technology (QUT, Brisbane, Australia) related to machine learning for particle laden fluid mechanics. QUT is a major Australian university with a global outlook and a 'real world' focus. We