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Physics faculty position” in the email subject. For more details, please refer to our website at https://www.phys.ncku.edu.tw/en/ . All supporting materials must be received by OCT. 15, 2026, for full
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Your Job You will develop, parameterise and validate physics-based battery models, initially focusing on test cells investigated under controlled laboratory conditions. Your work will combine
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develop a physics-informed digital-twinning approach to better characterize these dynamics and estimate relevant electrical and control parameters from transient voltage and current data. Your tasks will
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Your Job Develop a reinforcement learning (RL) controller for a liquid–liquid gravity settler, trained entirely offline in a simulated environment Use existing physics-informed neural network (PINN
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nanoelectronics research center IMEC ( https://www.imec-int.com/en ). The work will focus on spatially resolved electrical measurements, enabling direct correlation between structure and transport
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and interpretation of experimental data Your Profile You are studying physics, material sciences, engineering, or a related subject at a university and are looking for a topic for a master's thesis
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the understanding of reliability physics, and optimizing their potential down to deep cryogenic temperature. [1] https://irtnanoelec.fr/programme/q-loop-preparer-le-controle-commande-de-lordinateur
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, and physics-informed machine learning open new possibilities for establishing grid foundation models. However, it is still unclear which model structures is most capable and suitable, how well they
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research results at international conferences and prepare scientific publications Your Profile Master’s degree in physics or a closely related subject Solid background in quantum many-body theory and/or
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engineering, soil science, hydrology, plant science, environmental science, physics, engineering, applied mathematics or a related field Strong quantitative skills Interest in soil–plant water relations and