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At the Technical Faculty of IT and Design of the Department of Sustainability and Planning, Copenhagen, a position as Postdoctoral researcher in Geospatial Machine Learning for Predicting Land Use
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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Job Description If your background is in machine learning (ML) and you have a desire to make discoveries in health sciences, then this position as Postdoc is your possibility. In this collaboration
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quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
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We invite applications for a postdoctoral researcher to join the UMLFF project at the University of Luxembourg. The project aims to develop the next generation of uncertainty-aware machine-learning
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 2 months ago
Organization National Aeronautics and Space Administration (NASA) Reference Code 0202-NPP-MAR26-JPL-HelioSci How to Apply All applications must be submitted in Zintellect Please visit the NASA Postdoctoral Program website for application instructions and requirements: How to Apply | NASA...
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Polytechnic University (UM6P), Benguerir, Morocco, is seeking for a postdoctoral candidate in the area of machine learning for IoT networks. The candidate must hold (or about to complete) a PhD in the related
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 3 hours ago
Position Information General Information Position Number POST40 Working Title Post-Doctoral Fellow-Machine Learning in Thermal-fluid Sciences Division Academic Affairs Department College
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intelligence within grid-connected power converters and variable-frequency motor drives with edge computing and machine learning capabilities. We offer a multidisciplinary, international, and friendly atmosphere
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project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision or physics-informed machine learning, develop robust surrogate forward models to predict