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study the water imbibition in hierarchically porous Si?based material systems across multiple length and time scales. These systems can manipulate fluid transport through the tailoring of their porosity
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applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under various operating conditions and develop strategies
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performance in fuel cell (biogas) and co-electrolysis applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under
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. Correlated experimental, ab initio and multi-scale techniques are central to our mission: Development and application of advanced simulation techniques to explore and identify the fundamental structures and
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28.07.2023, Wissenschaftliches Personal Prof. Karen Alim’s group on Biological Physics and Morphogenesis at the TUM Campus Garching uses theoretical and experimental methods to investigate how flow
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discipline. You have experimental experience in soft matter, fluid physics, biological physics or a related discipline. You enjoy working in interdisciplinary and international teams and have basic programming