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project focuses on developing methods to assess the sustainability of nearly 100 nationwide AI systems within the National Lab on Education and AI (NOLAI). You will create methods to predict energy
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position within a Research Infrastructure? No Offer Description This PhD project focuses on developing methods to assess the sustainability of nearly 100 nationwide AI systems within the National Lab
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Department of Mathematics at Radboud University is seeking an outstanding, highly motivated PhD candidate in Mathematics of Nonlinear Acoustics. As a PhD candidate, you will develop novel mathematical methods
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dependent, and how to refuse tasks without undermining authority. You will use mixed methods, including qualitative research methods (such as interaction analysis) and quantitative research methods (such as
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ways of supporting learning. NOLAI co-creation projects identify such needs. However, there are not always existing methods to fulfil them. At the same time it also remains unclear what kind of methods
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area where the novel methods will be demonstrated. You will be part of the Probabilistic Graphical Models group at the Donders Centre for Cognition and of the interdisciplinary team of researchers and
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myelin water imaging and quantitative susceptibility mapping (QSM) and include vascular tissue factors. Your key responsibilities are: Develop and optimise neural network-based methods for MCR-MWI and
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. Research methods include computational modelling, brain imaging (fMRI), machine learning, behavioural methods, and other techniques. Virtually everything we sense, think and do is uncertain. For instance
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-cycle assessment to determine climate footprints, accounting for all emissions of the production, transport, and various end-uses. The prospective element allows assessment of technologies that are still
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on studies of visual perception and decision-making. Research methods include computational modelling, brain imaging (fMRI), machine learning, behavioural methods, and other techniques. Virtually everything we