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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
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during your bachelor, master and PhD courses. For more information about this function, please contact dr. K.E. Konrad, email k.e.konrad@utwente.nl, phone: +31 53 489 3906. About the department You will
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-based knowledge with machine learning. You will work closely with the Utrecht University team and OpenGeoHub together with other project partners, to develop and implement surrogate and hybrid modelling
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: 12 September 2025 Apply now Are you a data scientist interested in designing and implementing process-informed machine learning and uncertainties quantification methods? Join us as a postdoc and work
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: A PhD in Computer Science, Engineering, Mathematics, theoretical Physics or other degree programs from top universities involving at least one of the following topics: Machine Learning, AI, Dynamic
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative
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). The emergence of data-driven techniques (broadly grouped under the term “machine learning”) challenges the traditional foundations of controls and represents an alternative paradigm that cannot be ignored
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applications* in close collaboration with other discipline experts (software, microelectronics and applications engineers). * except for RF payloads. ** including artificial intelligence and machine learning