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drug testing program. Visa sponsorship is not avaiable for this position. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy
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management, parallel computing, and performance optimization while helping evaluate and introduce emerging technologies that advance mission capabilities. You will work alongside a multidisciplinary team of
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and teaches in the classroom, laboratory, and clinical settings. Under the direction of the EMS Program Director, the EMS Instructor is responsible for preparing, delivering didactic, and laboratory
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success. Basic Requirements: Ph.D. in Data Science and Engineering, Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a closely related field. Strong programming proficiency in
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 8 hours ago
experience. Citizenship Requirements: This opportunity is available to U.S. citizen and Lawful Permanent Residents (LPR) only. This program, administered by ORAU through its contract with the U.S. Department
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. Experience with 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
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limited to: HPC file transfer and parallel programming, among others. Benchmarking Computational physics Artificial Intelligence At the end of the internship, you will have the opportunity to present
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represent the organization by giving technical presentations to DOE program managers and in large public forums. Basic Qualifications: A PhD or equivalent experience in nuclear, mechanical, or chemical
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common scientific programming languages such as C++, Python, and/or Julia and version control systems. Experience in parallel programming with one or more common parallel programming models, like MPI
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, Python, or Ansible. Experience with performance tuning and benchmarking tools for HPC environments (e.g., Ganglia, Grafana, or similar). Experience with parallel programming frameworks (e.g., MPI, OpenMP