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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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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
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, starting 01.06.2026, ending 31.05.2030): Postdoc position (f/m/d) in the department “Competencies, Personality, Learning Environments” (Focus: socio-emotional and cognitive competencies) The Leibniz
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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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learning (AI/ML) being a major focus. Many of the laboratory's interests center around the identification of small molecules using mass spectrometry data, and the use of language models to predict
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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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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 23 days 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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on advanced machine learning and emulation approaches. Key responsibilities: The candidates will be expected to work on the following tasks: - Develop machine learning (ML) methodologies appropriate
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep