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paid. We expect the stipend to increase each year. Only Home students are eligible for funding. The start date is October 2026. The project aims to develop and optimize metal oxide aerogel materials
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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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-B4 Investigators: Prof. Dr. Meng Wang, Chair of Traffic Process Automation , and co-supervised by another expert in traffic control Requirements: excellent or very good university degree
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the Advanced Production Engineering (APE) research group that deals with the development, optimization and implementation of advanced production technologies and manufacture processes with emphasis on mechanical
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optimized for resource-constrained IoT edge devices, - And what role optimised computing architectures can play in executing these models efficiently. The project will be conducted in close
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Your job Are you committed to reducing food waste? Are you interested in how coordination, dynamic pricing and redistribution may affect food waste? Do you have a passion for applying optimization
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: Prof. Dr. Steven Travis Waller, Chair of Transport modeling and simulation, and co-supervised by at least one additional professor, plus an international tutor of the CRC Requirements: excellent
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the Advanced Production Engineering (APE) research group that deals with the development, optimization and implementation of advanced production technologies and manufacture processes with emphasis on mechanical
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, and energy solutions. By integrating electrochemistry with advanced materials and engineering, the unit delivers pioneering solutions with real-world impact. Led by Prof. María Cuartero (ERC Fellow) and
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and ground), and boasts expertise in controlling and deploying them in practice, as well as in designing coordination strategies for them. Our recent work on ML-based co-optimization demonstrates some