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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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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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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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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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(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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to extend the operational lifespan and reduce the overall weight of wind turbines. By innovating ways to lower mechanical loads on critical components and optimizing material usage, we aim to pave the way
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that help determine when an AI model is ready for use and when more research is needed. PhD in Epidemiology on value-of-information from validating clinical prediction models and AI Our goal: Develop value
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to blood pressure changes, electrolyte imbalances, seizures, and cardiac arrhythmias. No curative therapies are available, and current treatment remains symptomatic. Recently, we identified mitochondrial DNA