83 parallel-programming "U.S" Postdoctoral positions at Oak Ridge National Laboratory
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: Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or a closely related field. Strong programming proficiency in C, C++, and Python. Hands-on experience with embedded systems
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), and data-model integration, leveraging the U.S. Department of Energy’s (DOE) Leadership-Class Computing Facilities to advance predictive understanding of complex environmental systems. Major Duties
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welcome applicants with strong depth in one or more relevant areas and interest in collaborating across disciplines. As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL
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, adaptive control) Experience applying machine learning/AI to engineering systems Proficiency in programming and simulation tools such as Python, MATLAB/Simulink, and/or ML frameworks (TensorFlow
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programming in Python, GEE, or R, and working with modern scientific computing and/or AI/ML frameworks. Experience with analyzing large, heterogeneous environmental, geospatial, remote-sensing, or
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relations) Demonstrated strength in quantitative methods and programming (e.g., Python or R; reproducible workflows; version control) Experience or interest in AI/ML application to ecophysiological
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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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facilities to applications across all computational domains and disciplines. We are an inclusive dynamic environment that welcomes those with initiative and creativity. As a U.S. Department of Energy (DOE
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position. Experience with neutron transport and reactor analysis software (SCALE code system, MCNP, OpenMC, Serpent, VERA, MOOSE codes, etc.). Experience with common programming and scripting languages
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computer modelling systems such as finite element analysis (FEA),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive