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Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
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and with external academic partners #scientific publication and presentation Your profile #a Masters degree in oceanography, fluid mechanics, data science, or related disciplines #a strong academic
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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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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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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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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& further information Informal queries: Project page: www.tcd.ie/mecheng/research/fluids-acoustics--vibration/projects/noise-2050 Shape Ireland’s soundscape of the future - apply now and make your research
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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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, building energy and installation, solid mechanics, fluid mechanics, materials technology, manufacturing engineering, engineering design and thermal energy systems. Technology for people DTU develops
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development of special phase field and phase field crystal models coupling newly developed approaches with established approaches for simulating e.g. mechanical properties and the flow of fluids implementation