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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in investigating how smart AI-models are? Do you want to conduct research
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are focused on areas with high noise exposure: areas near the runway or final approach or early departure routes. Current noise models only consider a free propagation path from the sound source towards
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Vacancies PhD position on model-based wavefront shaping microscopy Key takeaways With wavefront shaping, you can focus light through non-transparent materials. Since the invention of wavefront
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work will provide the "ground truth" for the project. By simulating complex inflow conditions, you will create the high-fidelity datasets required to validate the Wind Field Forecasting (WFF) models
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traffic management. Model and assess the integration of hydrogen and electric aircraft into European airspace and support the EU Green Deal net-zero emissions goals. Job description We are seeking a
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is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily
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(LES) results. Key Responsibilities: Develop and refine numerical algorithms for real-time wind field forecasting. Validate forecasting models against high-fidelity LES data and field measurements
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for load forecasting in scenarios where current models fall short, such as extreme weather events, grid incidents and high variability in renewable energy. You will explore techniques including graph neural
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and validating AI models for load forecasting in scenarios where current models fall short, such as extreme weather events, grid incidents and high variability in renewable energy. You will explore
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deeper understanding of complex physical mechanisms. You are good at communicating and explaining the results of your work. Experimental (and modeling) experience in the field of tribology would be