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our community. We are now looking for a Doctoral Researcher in AI and Quantum-Inspired Optimization for Sustainable Energy Systems Are you passionate about developing AI-based and quantum-inspired
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opportunity to drive the development of system-level digital-twin and optimization methodologies—integrating electrolyzer models with renewable generation, power electronic conversion, energy and hydrogen
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will be paid to the development of robust and adaptive control strategies capable of operating under variable environmental conditions. The optimization of energy flows between renewable energy
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Electronic Systems. You will join an interdisciplinary team working across electrolysers, Power-to-X systems, power electronics, control, digital twins, and energy-system optimization, in close
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Applied Power Electronic Systems. You will join an interdisciplinary team working across electrolysers, Power-to-X systems, power electronics, control, digital twins, and energy-system optimization
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, physics-based simulations and energy-system optimization models. Investigate how tabular foundation models can support energy-system modelling and optimization , including applications such as prediction
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techno-economic analysis, life-cycle assessment, mathematical optimization, process-oriented modeling of industrial energy systems, and the analysis of regulatory frameworks. In particular, we focus on
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using building measurements , physics-based simulations and energy-system optimization models. Investigate how tabular foundation models can support energy-system modelling and optimization , including
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in energy systems engineering, with an emphasis on industrial energy systems, energy management, techno-economic analysis, modeling, simulation, optimization, and advanced control. The position will
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University. The Lizhou Fan group works on electrocatalysis, operando spectroscopy, and electrolyzer system optimization for sustainable energy conversion. The group focuses on understanding and