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to High-Fidelity Simulations – The project will use OpenFAST, FAST.Farm, and Digital Twin simulations for AI model validation. The student will have the opportunity to join a vibrant community and team
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tools (e.g., drones, 3D mapping) for high-resolution geological mapping and rock mass quality assessment. Develop and calibrate numerical models using field data and case studies to simulate various
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on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our employees to continue to invest in
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The University Medical Center Göttingen (UMG) unites the Medical Faculty of the Georg-August University and the University Hospital in an integration model. With around 9,700 employees, the UMG and
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engineering with TensorFlow or similar frameworks Ability to develop Spiking Neural Networks from scratch, including training and quantization Optimize and benchmark applications and models for neuromorphic
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challenges and decision-making under uncertainty. Ability to translate conceptual models to their mathematical formulation and to test them with numerical and simulation experiments. Excellent communication in
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can be varied. Crucially, the models we derive will be validated by real-world measurements to ensure our simulation environments are realistic and scalable to more complex radar networks. This will
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will transition in a second phase to white box approaches that result in interpretable models. For ground truth data, μCT data will be used. A similar approach will be applied using surface roughness
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modeling to simulate the pavement response under different loading conditions. The research will support improvements of the existing specification for the maximum authorized axle load and mass of vehicles
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treatment processes through advanced machine learning, validated against physics-based models and experimental data. 2. System Integration: Integrating the DTs into material and energy balance equations