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statistical and 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
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project, “Mathcrete”, and offers a unique opportunity to collaborate closely with another Postdoc specializing in 3D nano image reconstruction and modelling tools development, as well as other PhDs and
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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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systems (MEMS and NEMS). Prof. Vincenzo Esposito leads the project in the framework of a dynamic team in the Functional Oxides section. The FOX team possesses excellent competencies and the most advanced