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Field
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convergence of high-performance computing (HPC) and AI, which is a subject that sees an increasing importance due to the widespread use of AI and in particular machine learning (ML). As today’s mainstream AI/ML
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fellow will be part of a growing team of researchers, postdocs and PhD students working on intelligent observing systems using machine learning and data assimilation methods in the ACTIVATE project. UiO
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. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations of reactor transients and quantify how surrogate uncertainties propagate
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. The project is supervised by Associate Professor Ulysse Côté-Allard at the Department of Technology Systems, University of Oslo, whose research focuses on the development of machine learning algorithms
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Informatics and edge intelligence etc. Must have documented significant Knowledge/Research Background, or Must be able to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed
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of novel computational/biostatistical/machine learning methods for the integration of multiple, diverse dataset and the synthesis of hypotheses around the molecular mechanisms that drive the co-occurring
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effectively exploited, possibly using some kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several
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(kidney biopsy, serum, urine) for comprehensive biomarker profiling. Utilization of machine learning and image processing for advanced tissue analysis. The Herman B Wells Center for Pediatric Research
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simulations combined with physics-informed machine learning will also be examined. Several research and industrial partners are a part of this project. The ideal candidate would combine strong computational
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and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland Norway’s research group for User Perception and Engagement in XR