74 computer-science-intern-"https:"-"https:"-"U.S" positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
& Computing Center to support ORNL’s geospatial high-performance computing (HPC) research portfolio within the Geospatial Science and Human Security Division. ORNL is the nation’s geospatial research laboratory
-
on either a large-scale scientific research and development project or large scientific instrument project. Oak Ridge National Laboratory (ORNL) is the largest US Department of Energy science and energy
-
briefings or field visits. Uphold ORNL’s safety, quality, and ethics standards. Basic qualifications: Bachelor’s degree in any scientific, engineering, or related field (e.g., physics, computer science
-
, and biological systems. ORNL’s computational science research efforts enable scientists to efficiently implement these models at the extreme scale of computing and to store, manage, analyze, and
-
of education and experience may be considered. Expertise in computational material design, additive manufacturing, and material science is a plus. Preferred Qualifications: Such a candidate (1) demonstrates an
-
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
-
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
-
Requisition Id 15814 Overview: Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative
-
transfer risk for 1,000+ foreign engagement, official travel, and international visitor requests annually. Prepare risk assessment reports and help develop access management plans based on these risk
-
. This section will advance the integration of high‑performance computing (HPC), artificial intelligence (AI), data science, and automation with experimental biosciences to enable predictive, scalable, and AI