242 computer-science-intern-"https:"-"https:"-"https:" positions at Oak Ridge National Laboratory
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through papers, artifacts, and presentations at top-tier venues. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, a physical/computational science discipline (e.g., physics, chemistry
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analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section of the Computer Science and Mathematics (CSM) Division. CSM
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(S&T) capabilities (i.e., Earth, Environmental, and Atmospheric Science; Advanced Computing, Scientific Visualization and Data Sciences; and Earth and Energy Systems Infrastructure Analysis and
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complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section of the Computer Science and Mathematics (CSM) Division. CSM delivers fundamental and applied research
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of the Mathematics in Computation (MiC) Section of the Computer Science and Mathematics (CSM) Division. CSM delivers fundamental and applied research capabilities in a wide range of areas, including
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Qualifications: Ph.D. in electrical engineering, computer science, or related discipline completed within the last five years. Demonstrated expertise in computed tomography (CT), with experience in sparse-view and
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Requisition Id 15046 Overview: Oak Ridge National Laboratory (ORNL) is currently recruiting Active-Duty U.S. Military personnel for the DoD SkillBridge Internship Program. The program is 4-6 months
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Requisition Id 15385 Overview: We’re hiring a Group Leader in Neutron Systems Engineering to oversee critical computing infrastructure for data acquisition, analysis, management, and instrument
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program managers. Represent the Accelerator Science and Technology section to RAD, NScD, ORNL, and the broader external community. Support the mission of the Accelerator Institute to expand the application
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and algorithms needed to model complex physical, chemical, and biological systems. ORNL’s computational science research efforts enable scientists to efficiently implement these models at the extreme