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Requirements: very good or good university degree in physics, meteorology, fluid dynamics or comparable Description of the PhD topic: (subproject T7) In Urban air mobility, a high wind sensitivity of UAVs
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Technology and Logistics and co-supervised by at least one additional professor plus an international tutor of the RTG Requirements:very good or good university degree in physics, meteorology, fluid dynamics
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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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research team. Good knowledge and experience in heat and mass transfer is essential and proficiency in the use of Computational Fluid Dynamics will be considered an advantage. The student will benefit from
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Research theme: Fluid Mechanics, Machine Learning, Ocean Waves, Ocean Environment, Renewable Energy, Nonlinear Systems How to apply: How many positions: 1 Funding will cover UK tuition fees and tax
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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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degree in Hydraulic Engineering, Hydropower Engineering, Civil Engineering, Fluid Mechanics or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been
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Prof S He Application Deadline: 20 May 2025 Details We invite applications for a fully funded four-year EPSRC iCASE PhD studentship at the University of Sheffield, offered in collaboration with SLB, a
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thermochemical TES. Your main supervisor will be Prof Adriano Sciacovelli and you will join the Thermal Energy Section at DTU Construct. Your work will contribute to a paradigm shift in how complex TES systems
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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