50 computer-algorithm-"UNIS" Postdoctoral positions at Oak Ridge National Laboratory in United States
Sort by
Refine Your Search
-
, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science
-
Requisition Id 14907 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is
-
advanced sensing and controls algorithms for manufacturing Communicate research results through presentations, reports, conference papers, and peer-reviewed journals Deliver ORNL’s mission by aligning
-
computational models and systems using algorithms and analytics for materials and related physical sciences for a broad range of energy, transportation, and advanced manufacturing applications. Major Duties
-
challenges facing the nation. We are seeking a Postdoctoral Research Associate who will support the Quantum Sensing and Computing Group in the Computational Science and Engineering Division (CSED), Computing
-
Requisition Id 15305 Overview: The Computational Hydrology and Atmospheric Science (CHAS) Group at Oak Ridge National Laboratory (ORNL) is seeking a highly motivated Postdoctoral Research Associate
-
environmental conditions, and predicting photosynthesis at multiple scales. The selected postdoctoral scientist will work with a team of mathematicians, computational scientists, plant geneticists and
-
breeding blankets, including computational fluid dynamic (CFD), thermal hydraulic, and magnetohydrodynamic (MHD) analyses. We seek individuals with advanced analytical and computational skills who can use
-
safety at ORNL and DOE sites. This position resides in the Performance Engineering group in the Data and AI Systems Section in Computer Science and Mathematics division within Computing and Computational
-
Earth scientists, geospatial experts, and computational scientists to leverage leadership-class computing resources for large-scale model training, testing, and deployment. Knowledge Dissemination