89 python "Computer Vision Center" "Computer Vision Center" Postdoctoral positions at Oak Ridge National Laboratory
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modeling, plasma physics, and edge/scrape-off layer transport. Demonstrated programming ability and knowledge of Python and/or C++. Experience with deep learning frameworks like PyTorch and application
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, including energy-efficient building systems, thermal-fluid processes, industrial heating applications, data center thermal management, and other emerging energy technologies. Develop and operate
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(e.g., Python, C++, Matlab, JavaScript). Preferred Qualifications: As this position works in interdisciplinary fields, knowledge of codes in related disciplines, such as thermal hydraulics
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experience in nuclear, mechanical, or chemical engineering, engineering physics, or related field completed within the last 5 years. Experience with Python, C, and/or C++ applied programming
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atomic dynamics will be highly advantageous Basic knowledge of models of strongly correlated electron systems Proficiency with scripting or programmatic languages, such as Python, c, and matlab
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Qualifications: Ph.D. degree in Physics, Chemistry, Computer Science, or a related discipline. Strong foundation in quantum information and computational physics Preferred Qualifications: Experience in
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controlling hardware and data analysis using Python/Matlab. Experience with wet chemistry, chemical separations or studies of liquid interfaces. Excellent written and oral communication skills. Motivated
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, aligning, or characterizing optical systems for microscopy, spectroscopy, interferometry, or quantum-optics experiments. Experience acquiring and analyzing experimental data using Python, MATLAB
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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