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outcomes in peer-reviewed journals in a timely manner. Ensure compliance with environment, safety, health, and quality program requirements. Maintain strong dedication to the implementation and perpetuation
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to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation. ORNL offers competitive pay and benefits programs to attract and
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divisions and directorates with researchers and engineers to execute excising NNSA programs. Prepare and present periodic reports documenting research and development activities. Ensure compliance with
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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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, MCNP, Serpent, OpenMC, and/or MOOSE and familiarity with reactor systems and concepts. Programming/scripting experience including the use of one or more of C/C++, Python, Fortran, Git, and CMake an asset
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challenges facing the nation. ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee
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for building system dynamics models and for converting those models into probabilistic programs so their parameters can be inferred from data. The successful candidate will extend the mathematical and
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completed within the last 5 years or expected to be completed soon. Expertise in AI/ML methods in an environmental or Earth science context Experience programming in Python or related languages A strong
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or expected to be completed within the next six months. Experience in ecological modelling and/or Land Surface Modelling Knowledge and experience working in HPC environment. Programming experience in Fortran
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or expected to be completed within the next six months. Experience in ecological modelling and/or Land Surface Modelling Knowledge and experience working in HPC environment. Programming experience in Fortran