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, reliable and sustainable use of deep and shallow geothermal systems, it is essential to optimize them (borehole locations, sizing, operation, etc.). The resulting optimization problems are so-called PDE
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(DSGVO) regarding the collection and processing of personal data as part of your application: https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By submitting your application, you confirm that you
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machine learning technologies. This PhD position is part of the project “Artificial Intelligence for the automated creation of multi-scale digital twins of the built world”, which is funded via the Georg
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Materials” concentrates on the understanding of structure-performance indicators in electrocatalytic reactions. Our catalysts are the heart of sustainable energy conversion processes such as in hydrogen fuel
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Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By
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ecology (e.g. pollination, chemical or molecular ecology). • Strong experience with statistical data analyses. • Experience in or willingness to learn analytical chemical analyses and data processing
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as well as politics and power shape and are shaped by economic processes, focusing in particular on the causes and consequences of technological change. In doing so, it helps us understand how
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responses of mature beech and spruce to experimentally induced drought. Your task will be to elucidate key ecophysiological processes (e.g. xylem sap flow, stomatal conductance, resource allocation between
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decision-making in operational settings, aiming to enhance performance and optimize decision processes. Collaboration opportunities with industry partners are available, providing a strong mix of academic
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information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm