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in the area of probabilistic methods in machine learning. These include applications of Random Matrix theory and Gaussian processes to Deep Neural Nets. Teaching may be required. Education and
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related field by the appointment start date. The successful candidate will also have: A strong background in numerical modeling and the application of computational methods to land surface hydrological
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on cutting-edge research projects involving design, analysis and implementation of advanced numerical methods and algorithms in interdisciplinary applications. The position includes the possibility
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