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machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital co-simulation
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on exploring the evolution of magnesium-based binders in different environments, with particular interest in carbonation mechanisms. You will gain hands-on experience with advanced equipment and computational
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research related to fluid mechanics, structural dynamics, or related fields. Knowledge of experimental testing, calibration procedures, and data analysis for wave-related research. Strong scientific writing
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-based simulation for process optimization. Developing advanced numerical models for the coupled heat and mass transfer in the float zone process including 3D computational fluid dynamics (CFD) models