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to improve the power density and energy efficiency of redox flow batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e. complex
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affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from
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application! We are looking for a PhD student in Medical Science. Your work assignments Your work will entail the investigation of how Wnt signaling, a cell-to-cell communication pathway conserved across
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. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
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that enable energy-intensive industries to plan and optimize their production based on energy demand, power consumption, and sustainability. The current PhD position focuses on analyzing how digitalization and
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. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
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Are you passionate about advancing sustainable mobility solutions? Do you enjoy working at the intersection of artificial intelligence, optimization, and energy management? We invite applications
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and is implementing industry-academia partnerships through collaborative projects and strategic initiatives. About the research project Lithium-ion batteries currently dominate rechargeable energy