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power electronic design, modelling and simulation tools, and hardware development Knowledge of digital control implementation, testing, and characterization of power electronic components is expected
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focus on developing a molecular- and system-level understanding of CO₂ capture and release in e-DAC systems using computational modeling and simulation. The PhD candidate will apply computational
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power electronics. Experience with power electronic design, modelling and simulation tools, and hardware development Knowledge of digital control implementation, testing, and characterization of power
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generator (WTG) simulation model, and a grid-forming type-4 WTG model without or with an energy storage system. The main research target is to evaluate the grid-forming capability of a wind turbine generator
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understanding of molecular thermodynamics, and realize the importance of different types of properties in selecting and developing the most physically sound thermodynamic model for water and electrolytes
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with different control technologies, such as developing a typical grid-following type-4 wind turbine generator (WTG) simulation model, and a grid-forming type-4 WTG model without or with an energy
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on reinforcement learning (RL) for policy discovery in a multi-sector “integrated modeling environment” that connects fast ML metamodels of simulators (e.g., transport, energy, environment, climate events). The aim
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their properties. This PhD project seeks to uncover fundamental understanding of the vibrations in these materials to overcome this limitation. The PhD candidate will establish computational models of a range of
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how these factors influence performance, safety, and lifetime predictions. Your research will involve constructing probabilistic and statistical models—such as Bayesian inference, stochastic simulation