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Postdoc in modelling Greenland and Himalaya precipitation using machine learning Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 26
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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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Vacancies PostDoc Fellowship: Real-time ultrasound-based control of bionic legs Key takeaways Our mission is to enable intuitive control of powered ankle prostheses for amputees through real-time
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models (e.g. mixed-effects regressions, Bayesian analyses). You preferably have experience supervising and/or teaching students. You preferably have knowledge of swarm robotics and/or deep learning
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anthropology, sociology). You are eager to engage with fundamental questions about language and technology. You bring solid technical skills and deep, critical understanding that you wield for thoughtful
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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