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in computational research Comprehensive understanding of quantum mechanics and electronic structure theory is critical Experience with CFD (e.g., the use of OpenFoam or ALDFoam) and microkinetic
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, and past experience at publishing in technical journals. Education Ph.D. in Mechanical, Chemical, Materials Engineering or related field. Experience Applicants should have extensive experience in
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interdisciplinary teams that involve experimentalists and modelers Criteria of the candidates: PhD in Chemical/Mechanical Engineering, Applied Chemistry, Applied Mathematics, Physics, or related disciplines, with
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objective will be achieved using engineering and CFD tools capable of addressing high-speed, turbulence, transition, high-speed combustion, and the thermo-mechanical coupling with the thermal protection and
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experimental results. Ability to work in interdisciplinary teams that involve experimentalists and modelers. Criteria of candidates: PhD in Chemical/Mechanical Engineering, Energy, Applied Chemistry, Applied
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opportunities for teaching and service-related activities to successful candidates. Required Qualifications • Ph.D. in Aerospace or Mechanical Engineering by the time of appointment • Demonstrated expertise in
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, energy engineering or a closely related discipline. Experience in modeling & simulation of three-dimensional multiphase turbulent reacting flow applications using 3-D CFD codes (e.g., CONVERGE, OpenFOAM
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, project presentations, and other regular channels. Position Requirements This level of knowledge is typically achieved through a formal education in chemical engineering, mechanical engineering, or a
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external project partners. Minimum Qualifications: Ph.D. degree in Mechanical and Aerospace Engineering, Chemical and Process/Systems Engineering, or other related fields. Preferred Qualifications: Strong
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 3 days ago
is reproduced in the NASA Ames Electric Arc Shock Tube (EAST) facility, and is used to test models developed to predict the heating mechanisms. The primary models employed are the DPLR computational