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geometry manipulation with computer-aided design software. Experience with coupling CFD and FEA codes. Knowledge of multi-dimensional code development (in C++/C/Fortran) for two-phase/multiphase flow and
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in spatial analysis and data visualization Computer programming skills relevant for data manipulation and analysis Experience with creating and using complex data-driven analytical models using R
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combustion engines. Experience with CONVERGE CFD software. Experience in geometry manipulation with computer-aided design software. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long
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using software, such as LAMMPS, and machine-learned potentials Experience in GPU programming with Kokkos An understanding of computer architecture and experience in the analysis and improvement
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computer vision. Experience with multi-modal data fusion and alignment techniques. Experience with spatial transcriptomics or other -omics data analysis. Proficiency in Python programming and scientific
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for such models include high-resolution 3D imaging, time-resolved materials characterization, and atomic structure determination. Scientific instrument data is often multimodal in nature and developing DL models
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A postdoctoral position on exascale atomistic simulations, AI/machine learning and data analysis of ferroelectric devices is available immediately at the Center for Nanoscale Materials (CNM
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the scientific discovery process by quickly extracting useful information from vast quantiles of data, and by providing feedback to the experiment system enabling autonomous control and steering. New fast data
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The Materials Science Division (MSD) of Argonne National Laboratory is seeking applicants for a postdoctoral appointee in experimental x-ray and materials science. Although exceptional candidates in
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Argonne is a multidisciplinary science and engineering research center, where talented scientists, engineers, and business professionals work together to answer the biggest questions facing humanity