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to ORNL's Research Code of Conduct. Our full code of conduct and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity . Basic Qualifications: PhD in
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experience in scientific data visualization, AI/ML, or a related field. Proficiency in the Python and C++ programming languages. Preferred Qualifications: Strong publication record with publications in
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, Fortran, MATLAB, R, Python, Julia, or related languages. Experience with high-performance scientific computing. The ability to obtain and retain a national security clearance. Application Requirements: A
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distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and parallel computing. Demonstrated hands-on experience and
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, statistics or a related field. Proficiency in Python and C++ programming languages. Excellent written and oral communication skills. Preferred Qualifications: Strong publication record with publications in
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(HPC), or large-scale data analysis. Experience in applying AI/ML techniques to hydrological and Earth sciences. Proficiency in scientific programming languages such as Python, Julia, R, Fortran, or C/C
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statement from the Lab Director’s office can be found here: https://www.ornl.gov/content/research-integrity Basic Qualifications: PhD in physics, computer science, engineering, or a related field with at
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professional experience such as internships in industry or national labs, participation in visiting research programs, etc. Software development experience in C++, C, Fortran, MATLAB, R, Python, Julia
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Engineering, Mechanical Engineering or a closely related field completed within the last 5 years. Experience in computational modeling, experimental research, or both. Experience with Python, MATLAB, or other
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. To support ORNL strategic research and development activities at the Manufacturing Demonstration Facility (MDF) (https://www.ornl.gov/facility/mdf/ ), we are accepting applications for Postdoctoral Research