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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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industrial and academic partners. The overall goal of the project is to optimize the design of water eletrolyzers for efficient green energy production. You will be conducting Computational Fluid Dynamic (CFD
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industrial and academic partners. The overall goal of the project is to optimize the design of water eletrolyzers for efficient green energy production. You will be conducting Computational Fluid Dynamic (CFD
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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
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of new ideas based on knowledge and insight. The simulation tools can be broadly applied, covering disciplines governed by physics(solid mechanics and fluid dynamics) to discrete event simulation