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, this research project will focus specifically on how multiple grid converter-interfaced assets should be controlled and coordinated in an inertia-less (or almost inertia-less) isolated power network, to ensure
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contribute to the development of digital twins of propellers and explore collective learning approaches, where multiple propellers cooperate for optimal flight control. The PhD will be carried out in joint
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of Econometrics and Statistics, esp. in the Transport Sector and co-supervised by Prof. Dr. Klaus Bogenberger, Chair of Traffic Engineering and Control, TU Munich. Requirements: Excellent, very good or good
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will closely cooperate with the PhD student at GFZ in order to link the interpretation of geodetic GNSS measurements with the modelling of glacial-isostatic adjustment (GIA). You will focus your work
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. Candidates must be able to demonstrate ability to publish scientific articles. Applicants must be able to work independently and in a structured manner and have the ability to cooperate with others. Applicants
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(subproject B4 - Multiobjective optimization of traffic signals for multimodal traffic): This project aims to develop a cooperative and adaptive traffic signal control approach that addresses the needs
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chemical technology, chemical engineering, material science, nano-materials or related areas. Very good command of written and spoken English. Motivation, communication and cooperation skills, pro-active and
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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optimization. Experience with energy system modeling - ideally of large scale multiple country energy systems, PtX and renewable fuel production. Strong writing and presentation skills. A willingness and desire
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scale multiple country energy systems, PtX and renewable fuel production. Strong writing and presentation skills. A willingness and desire to engage in interdisciplinary collaboration and teaching. Good