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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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Biology: Strong background in systems biology and regulatory network modeling Interdisciplinary Collaboration: Experience working across disciplines with computational biologists, computer scientists, and
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engine modeling code. Perform high-fidelity CFD simulations of turbulent and reacting flows pertaining to gas turbines and detonation engines using spectral element method (SEM). Perform scalability
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We are seeking a highly motivated and flexible postdoctoral researcher to join the Applied Materials Division (AMD) at Argonne National Laboratory to develop advanced methods for in situ and
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of advanced scanning/transmission electron microscopy (S/TEM) methods for cutting-edge scientific research in areas such as quantum materials and low-dimensional energy systems. This position emphasizes