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support the optimization of hydrogen storage systems. · PhD in fluid mechanics, energy engineering, chemical/process engineering, or related field · Strong background in Computational Fluid Dynamics (CFD
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, scientific computation, scientific software and algorithm development, and data analysis; demonstrated ability to conduct original, high-quality research in computational fluid dynamics and/or computational
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. The work combines physics-based thermal design and process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the final design
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, this role will contribute to studies focused on underwater vehicle manoeuvring and resistance. In this position, you will undertake advanced Computational Fluid Dynamics (CFD) simulations, primarily based
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: atmospheric convection, radiative transfer, climate change, atmospheric/fluid dynamics, or machine learning. Proficiency in numerical analysis and high-performance computing. Experience with atmosphere/climate
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Requisition Id 16949 Overview: We are seeking a Postdoctoral Research Associate who will focus on efforts related to gas dynamics, fluid flow, and mass transfer. This position resides in the Applied
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complex environmental datasets. Knowledge, Skills & Abilities: Advanced knowledge of physical oceanography, geophysical fluid dynamics, numerical methods, or closely related principles relevant to physics
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 5 days ago
Engineering, Physics, or related field. Technical Skills (Required) • Demonstrated experience with computational fluid dynamics (CFD) • Demonstrated experience with DSMC • Strong background in rarefied gas
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sequence and to model the evolution of body size using bounded evolutionary models. 3) Biomechanical and Hydrodynamic Modeling: Apply computational fluid dynamics to test hydrodynamic hypotheses related
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 2 months ago
ground. Ad-hoc choices for model noise can fundamentally disrupt the corresponding fluid dynamics models, leading to unrealistic properties. Rigorously justified methodologies for deriving stochastic