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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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data driven approaches (experimental dataset physics based model dataset) to achieve process optimization, defect prediction and property prediction in various AM processes. The additional specific
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research in radiochemical separations and advanced aqueous recycling of used nuclear fuel (UNF). The successful candidate will contribute to the development and optimization of advanced aqueous recycling
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, qualification, and deployment of AI agents and models, Computational Fluid Dynamics (CFD) simulation codes, and Finite Element Method (FEM) based tools for nuclear energy (fission and fusion) applications
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, calibration, and application. Experience with computational methods including steady-state modeling, dynamic simulation, computational fluid dynamics (CFD) to support system design and performance optimization
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, conduct experimental campaigns, perform materials synthesis and analysis, sub-component fabrication, process optimization and integration, and prepare technical documents and research publications. Present
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members with expertise in mechanical engineering, fluid dynamics, electrical engineering, and biomaterials. In addition, there are 9 full-time staff members specializing in computational methods, in vitro
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 2 hours ago
. Fluid Characterization will involve Pressure-Volume-Temperature (PVT) measurements, characterizing additives such as surfactants, optimizing additives, quantifying stability and reactivity of additives
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 18 days ago
and aerodynamics through the use of comprehensive analysis, high-order computational fluid dynamics (CFD), and direct numerical simulation (DNS) tools. The postdoctoral researcher will work with CAMRAD