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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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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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thesis, previous experience with neuroimaging, numerical mathematics, optimization, inverse problems, software development, motivation and research interests. The location for this research will be
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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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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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for a PhD position that combines research in the field of intelligent mission planning and learning-based optimization with real-world applications, in collaboration with Volvo Group. This is an ideal
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multidisciplinary environment. PhD Research Focus The selected PhD student will contribute to the design, fabrication, and optimization of electrochemical devices, exploring novel electrode materials, miniaturization