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available validated DEM simulation models and enriched by operational equipment performance data. To this end, physics informed machine learning techniques will be used to bring model data and real data
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promising solutions. This project aims to enhance SDB accuracy through deep learning pan-sharpening and physics-informed machine learning techniques. These methods will be tested in two regions worldwide and
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13 Feb 2024 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Physics Researcher Profile First Stage Researcher (R1) Country Netherlands Application
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13 Feb 2024 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Physics Researcher Profile First Stage Researcher (R1) Country Netherlands Application
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10 Apr 2024 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Physics Researcher Profile First Stage Researcher (R1) Country Netherlands Application
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. Here, we focus on zero-defect manufacturing processes for resilient and adaptable data-driven additive manufacturing. We will work with CEAD who have developed an additive manufacturing process combined
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. The successful candidate holds a MSc. degree in computational science, applied physics, mechanical engineering, chemical engineering or a similar degree. Some experience with coding (Python, Fortran, C++ etc.) is
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13 Apr 2024 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Physics Researcher Profile First Stage Researcher (R1) Country Netherlands Application
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6 Apr 2024 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Physics Researcher Profile First Stage Researcher (R1) Country Netherlands Application
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regulation and development on the one, and macroscopic stimuli (light, touch) on the other hand. We use tools from statistical physics, information theory and non-linear dynamics to understand the how well a