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and startups. It is committed to excellence in research and teaching, interdisciplinary education, and the active promotion of promising young scientists. TUM benefits from the healthy mix of companies
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made from magnetoelectric materials, which transduce wireless magnetic powering signals into local electric signals that can be used to stimulate neurons. Our multidisciplinary group works in materials
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wellbeing. They will use modeling approaches to combine natural and social science data. You will focus on developing and implementing mixed modeling approaches to test pathways through which structure
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. Furthermore, we aim to extend the framework with mixed-precision approaches, which will be implemented and analyzed. Secondly, we aim at a volume coupling of the high-performance packages waLBerla, HyTeG, and
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, or electrochemical CO2 reduction. To do so, the preparation of novel catalyst materials is of pressing concern. You will continue our research line around the preparation of novel catalysts based on mixed metal alloys
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19.07.2022, Wissenschaftliches Personal The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current
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the healthy mix of companies and startups of all sizes headquartered in the region and is tightly connected to regional research hospitals. The university also forges strong links with companies and scientific
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in the vicinity to the vibrant city of Munich, very well connected by train (ca. 30 minutes), and a perfect starting point to explore the Bavarian Alps and the rest of Germany. Working hours are
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to control of infection. The focus of the project is on virus-specific CD8 T cells and the local hepatic regulation of their effector functions through environmental and cytokine-induced signals. The AG
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Munich, very well connected by train (ca. 30 minutes), and a perfect starting point to explore the Bavarian Alps and the rest of Germany. Working hours are flexible and remuneration is in accordance with