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. The position involves the development and application of high-fidelity computational fluid dynamics (CFD) methods, theoretical modeling, and data-driven approaches to study turbulence, aero-thermo-acoustics, and
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of compressible flow regimes, including supersonic and hypersonic flows, as demonstrated by application materials. Familiarity with machine learning or data-driven modeling approaches in fluid dynamics, as
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electrolytes for high-energy-density redox flow battery application. The PI seeks individuals who are motivated and have research experience and knowledge of electrochemistry, electrochemical analytical
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