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models. Through the use of decentralized edge computing, cloud-based analytics, and existing seismic networks, the project aims to improve rapid decision-making and resilience assessment during and after
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modeling, optimization, and/or data analytics. Description of the PhD topic (subproject C1 - New metrics for transportation system appraisal): Transportation systems must deliver “function” (i.e
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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of inorganic ions and organic matter can cause defects in electrolyser stacks, resulting in costly process disruptions. This project considers: i) development of analytical methods for the quantification
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under civil law in Freising, is a research institution of the Leibniz Association that combines methods of biomolecular basic research with analysis methods of bioinformatics and analytical high
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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: excellent university degree (diploma, master's degree) in transport or related study programs with a solid basis in transport, data science, and/or data analytics; or equivalent practical experience
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of biomolecules which can only be successfully tackled by employing a variety of different theoretical methods. In this respect, this joint graduate college brings together the expertise in analytical theory from
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research proposal required for application with a timetable for the four-year research project. Required equipment will be set up and further development of relevant analytical methods will follow
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chemical evolution in the magma reservoir. The geochemical composition, isotopic tracers and the physical properties of the magmas are examined analytically and experimentally. They make it possible