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development of next-generation computational tools for simulating particle-laden two-phase flows by integrating advanced Artificial Intelligence (AI) techniques with traditional computational fluid dynamics
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looking for your next challenge? Do you have a background in machine learning or fluid dynamics and an interest in applying your skills to understand the dynamics of Earth’s fluid core and space-weather
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looking for your next challenge? Do you have a background in machine learning or fluid dynamics and an interest in applying your skills to understand the dynamics of Earth’s fluid core and space-weather
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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This is an exciting opportunity to join a new thrust to develop state of the art very high order computational fluid dynamics frameworks for high performance heterogeneous computing systems, working
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, mechanical engineering, or related subject with a record of publishing in high-quality journals. Good skills in applied Computational Fluid Dynamics (CFD) methods and proven experience of leading research
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, mechanical engineering, or related subject with a record of publishing in high-quality journals. Good skills in applied Computational Fluid Dynamics (CFD) methods and proven experience of leading research
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observations. You will work in close contact with Professor Rainer Hollerbach in the Department of Applied Mathematics, and will join the Astrophysical and Geophysical Fluid Dynamics research group, which is
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applications for a postdoctoral research fellow position. The successful candidate will focus on the discovery and design of immersion cooling fluids using molecular simulation and machine learning methods
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Postdoctoral Research Fellow in Computational fluid mechanics and physics of porous media Apply for this job See advertisement About the position Position as Postdoctoral Research Fellow available at the Njord