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The Multi-Physics Computations group at Argonne National Laboratory is seeking to hire a postdoctoral appointee on the topic of CFD modeling of internal combustion engines fueled by low-carbon fuels
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, computational sciences, physical sciences, or mathematics, together with sufficient specialist knowledge and hands-on experience in the CFD simulation of internal combustion engines, and in particular in-cylinder
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research will involve synergistic collaborations with a multidisciplinary team involving engine modelers, computational fluid dynamics (CFD) experts, and computational scientists to enhance the predictive
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for CFD to help the energy transition and look forward to meeting you and work on this challenging topic together! Job requirements As our new colleague you: Hold a PhD degree in an engineering or
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seeking a Postdoctoral Research Associate to assist in the development, qualification, and deployment of Computational Fluid Dynamics (CFD) simulation codes, methods, and standard processes for thermal
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The Multiphysics Computation Section at Argonne National Laboratory is seeking to hire a postdoctoral appointee for performing multi-physics and multi-scale CFD simulations of aviation gas turbine
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effort on active research projects and publish and present research results. Research work will focus on Computation Fluid Dynamics (CFD) models involving multiphase reacting flow simulations with emphasis
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Associate: Physics- Informed Data Driven Windfarm Modelling For this position the research activity will apply and advance on fast CFD methods for full wind farm simulation based on Large-Eddy-Simulation
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 2 hours ago
into the CFD and radiative codes in a tractable manner that could be used for future studies of entry systems. Field of Science: Interdisciplinary Advisors: Brett Cruden Brett.A.Cruden@nasa.gov (650) 604-1933
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multidisciplinary team comprised of fellow postdoctoral appointees, experimentalists, and staff scientists, with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with