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. This will include a detailed assessment of existing methods to address such risks, and on how to achieve a better use and exchange of existing protocols and data. The project includes the use of Digital Twins
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contributing to new research methods in human-AI collaboration? Then we are looking for you! We are hiring a technically strong, creative, and socially motivated PhD candidate to join the international
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of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to invent, develop and evaluate novel methods for pre-training and fine-tuning of perceptual foundation
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edge applications. Tasks and responsibilities: Develop new deep learning, computer vision and multimodal learning methods for pre-training and fine-tuning perceptual foundation models. Actively
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existing methods to address such risks, and on how to achieve a better use and exchange of existing protocols and data. The project includes the use of Digital Twins to simulate cascading disaster effects
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. We will achieve this together by creating the first mathematical framework for explainable AI and developing new explanation methods. This will involve using tools from mathematical machine learning
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, monitoring, and response to NaTech disasters, such as flooding or earthquakes that affect critical infrastructure installations. This will include a detailed assessment of existing methods to address
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have control over our spatiotemporal sampling of observational data locations, we first define the population. Next, we sample population units for (1) design-based estimation of population parameters
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units for (1) design-based estimation of population parameters, such as the mean and standard deviation of some target property or for (2) model-based prediction (i.e., mapping) of environmental
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on your background, the work will 1) focus on the interaction between microwave design and measurement methods, looking deep into the technological capabilities of GaN, or 2) focus on new methods