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charging strategies for lithium-ion batteries. The goal is to integrate model-based (digital twin) and data-driven (AI) methods to design and experimentally validate optimized pulse charging protocols. A
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of teaching qualifications. Depending on which faculty you are applying for employment, please see guidelines for teaching portfolio at The Technical Faculty of IT and Design, The Faculty of Engineering and
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for lithium-ion battery testing integrated with an EIS system. Through design-of-experiment, the setup will be employed for controlled aging of the cells. Diagnostics and characterization will follow, including
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