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standards for the use (and development of policy around) AI in disaster management. In parallel, Fraunhofer HHI is contributing to the Working Group on Digital Transformation for Hydrology and Water Resources
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that captures relevant features at different length scales and integrates them into a single reconstruction volume. This PhD project focuses on learning-based phase retrieval in the weak holographic regime
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. Therefore, we need an imaging scheme that captures relevant features at different length scales and integrates them into a single reconstruction volume. This PhD project focuses on learning-based phase
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Position Announcement At Utah Valley University, this advising role offers the opportunity to make a meaningful difference in students’ academic and personal success across every stage
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strategies for large-scale or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data pipelines for high
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; molybdenum, Mo,…) are ultimately derived from the transformation of soil minerals into secondary phases such as cation-poor clays and oxides, a process known as chemical weathering and taking place in soils
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MVPs (Minimum Viable Products) and scalable systems. Execution of technology testing and validation processes to ensure market readiness. Interdisciplinary collaboration: Partnering with Product Venture
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degradation and combustion of these fuels. The thermal degradation of solid biomass has been extensively studied in the literature, particularly at low heating rates, in order to identify the different stages
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stimulation, using custom cryo-plunging and high-pressure freezing instruments. In parallel, we are working to achieve multicolor electron imaging via cathodoluminescence—electron-beam–induced optical emission
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scale hydrological models The project offers the unique opportunity to connect novel processing and inversion techniques to experimental data from different regions and link the findings to relevant