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metamorphic conditions, the exact mechanisms (dissolution–precipitation vs. dynamic recrystallization vs. mechanical transport vs. partial melting), the extent of mobility and role of fluids remain debated
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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element modeling, computational fluid dynamics). Knowledge of heat and mass transport processes in heat-sensitive materials and process optimization. Experience in supply chains and hygrothermal
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development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria A knowledge of fluid dynamics is recommended. Personal
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. You will be part of an annual cohort and will receive training at different universities and industrial partners providing world-class facilities in a supportive, innovative, inclusive and interactive
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of complex, dynamic flows relevant to closely coupled engine aircraft configurations. You’ll join a pioneering multidisciplinary team that values equity, diversity, and inclusion, gaining unique expertise in
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24.02.2020, Wissenschaftliches Personal The research group “Fluid Dynamics of Complex Biosystems” headed by Prof. Dr. Natalie Germann has an open PhD position in the field of experimental rheology