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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 15 days ago
engineering (within the past 3 years) with a strong background in particle-based (kinetic) and fluid (continuum) methods for the modeling and simulation (M&S) of dense and rarefied ionized gas flows. Candidates
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 15 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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given to candidates who can start at this time). This position is funded through a project to research on roadway hydraulic structure perform, such as culvert, through computational fluid dynamics (CFD
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SPECIFICS The Artificial Heart and Cardiovascular Fluid Dynamics Lab at The Pennsylvania State University has a Postdoctoral Scholar position open in the field of cardiovascular mechanics. Candidates who have
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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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/139860 Requirements Specific Requirements 2.3 Candidate Profile Applicants should hold a PhD in Thermal Sciences, Energy, Fluid Mechanics, or a closely related discipline. The ideal candidate should
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progression and patient heterogeneity through deep molecular phenotyping. STEpUP OA integrates demographic, clinical, and synovial fluid proteomics with a particular emphasis on identifying pathways associated
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fluid handling systems, centrifugal contactors, sample preparation methods, and instrumentation, to support advanced aqueous recycling of UNF Evaluate separations performance for actinides, lanthanides
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integrates demographic, clinical, and synovial fluid proteomics with a particular emphasis on identifying pathways associated with structural damage and knee pain. What We Offer As an employer, we genuinely
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the simulation of turbulent flows using a tensor network representation of the Navier–Stokes equations. Unlike recent approaches based on tensor networks, which simulate fluid flows in physical space using finite