406 programming-"https:"-"https:"-"https:"-"https:"-"CSIC" positions at Oak Ridge National Laboratory
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performance tuning and benchmarking tools for HPC environments (e.g., Ganglia, Grafana, or similar). Experience with parallel programming frameworks (e.g., MPI, OpenMP, CUDA) and high-performance interconnects
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, safety, health and quality program requirements Maintain strong commitment to the implementation and perpetuation of values and ethics Deliver ORNL’s mission by aligning behaviors, priorities, and
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publish scientific results in peer-reviewed journals on time. Ensure compliance with environment, safety, health, and quality program requirements. Maintain strong dedication to the implementation and
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-reviewed journals in a timely manner. Ensure compliance with environment, safety, health, and quality program requirements. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our
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broader mission 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
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to export control requirements. Successful candidates must be qualified for such access without an export control license. About ORNL: ORNL offers competitive pay and benefits programs to attract and
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for energy, environmental, and security challenges facing the nation. ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The
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Qualifications: Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field Strong programming skills in C++, Python, or similar scientific computing
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senior technical staff to develop new motor concepts focused on achieving specified targets, both at a motor and system level. Be versant in various modeling and simulation programs as
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networks and beyond) and quantum physics Familiar with programming languages and scientific computing Preferred Qualifications: Experience working with low-rank linear algebraic approximation methods