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properties. In this project, we will apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and
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apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and Materials Theory division, a
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application! Work assignments The Division of Automatic Control at the Department of Electrical Engineering invites applications for a postdoctoral position in optimal motion planning and model predictive
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remanufactured. The established process is optimized considering the chemical process solutions during electrode washing. Finally, the process is evaluated regarding potential for scaling to larger battery formats
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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inverse design, optimization, and/or machine learning for designing and optimizing devices in integrated photonics, which will be subsequently fabricated and tested by our experimental partners in Metapix
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of the position is to develop the independence as a researcher and to create the opportunity of further development. The research tasks include the optimization of cultivation processes and freeze-drying
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the last three years prior to the application deadline Strong expertise in at least one of the following: power system optimization/digitalization, or power electronics hardware. Experience in digital
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. The goal is to create a design guide for municipalities and consultants, based on findings from the Chalmers Gårda raingarden pilot , to effectively treat polluted stormwater. The study will identify optimal
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the Department of Energy Sciences. At the division, we conduct research in various fields, including research in design and optimization of turbomachinery, reactive fluid dynamics, multi-phase and turbulent flows