36 parallel-programming-"Fields-Institute" Postdoctoral positions at Oak Ridge National Laboratory
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predictive analysis. Expereince with the Python programming language. Ability to work within a multi-disciplinary team environment on scientifically challenging problems. Demonstrated ability to communicate
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, EBSD, and X-ray CT Interest in working at the intersection of material science, advanced manufacturing, and digital manufacturing Programming skills using Python or modern C/C++/C# Demonstrated
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DL frameworks, programming in Python (preferred), NLP packages and pipelines, usage and understanding of basic Machine Learning algorithms and tools. Solid record of productive research demonstrated
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Postdoctoral Researcher in the fields of uranium chemistry and nuclear forensics. The role entails performing and leading cutting-edge research on nuclear fuel cycle-related materials with a focus on
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, SOLPS, UEDGE, SOLEDGE, or similar. Experience with plasma-material interactions, including models for sputtering, impurity transport, and sheath physics. Programming experience in Python, MATLAB
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experience working in HPC environment. Programming experience in Fortran, Python or R Experience in manipulating and analyzing large observation data or model outputs Working knowledge of terrestrial
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Monte Carlo radiation transport software and applications Experience with numerical computing using programming languages such as C++, Python, etc Author or co-author of open literature publications
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. Experience in C/C++, Matlab, and Python programming. Experience in power systems software like PSCAD, PSS/e. Preferred Qualifications: Experience with software development. Experience with use of GPUs
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associated publications. Experience using SCALE, VERA, MCNP, Serpent, OpenMC, and/or MOOSE and familiarity with reactor systems and concepts. Programming/scripting experience including the use of one
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software in Python and in the design and implementation of deep learning algorithms. Expertise in object-oriented programming, scripting languages, and modern software engineering practices for research