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Field
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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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the Research Group “Nonlinear Optimization and Inverse Problems” (Head: Prof. Dr. D. Hömberg) starting as soon as possible. The project is part of a BMBF project concerning industrial scale data preparation
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Collaborative
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collaborate with PhD and postdoctoral researchers whose work focuses on optimal electricity market participation and grid stability /synthetic inertia from BESS, respectively. You are expected to take a
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the field of intelligent systems and AI-integrated electronics. Aiming to create sustainable electronic systems, this research will develop energy-aware computing solutions that optimize power consumption and
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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In this project, different optimal control problems will be considered under a contagious financial and insurance market with regime switching and risk uncertainty. In the first chapter, an optimal
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performance and use market behavior and feedback to improve and optimize profitability. Serving as a hybrid between traders and researchers, Quantitative Systematic Traders focus more on alpha monetization
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, and systems optimization. The candidate will work actively as part of the Water Transport Systems and Stormwater Management research group . This position offers the opportunity to advance innovative