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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
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optimization, cell component manufacturing, and the testing of solid-state battery performance. This role involves intense collaboration with international partners and the dissemination of results within the EU
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optimization of single-phase LCL filter inductors taking into account dynamic hysteresis models for different magnetic core materials. Supervisor: Prof. Paavo Rasilo (Electromechanics) Secondments: Université
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chemical activation method, and develop environmentally friendly electrolytes. Work will focus on: Preparation, characterization, and optimization of porous carbon electrode ink for supercapacitor
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, simulation environments and optimal control are appreciated. English language requirements: Proficiency in written/spoken English is mandatory. In certain cases, we may ask for a language certificate. We offer