Sort by
Refine Your Search
-
Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate who will support the areas of multimodal imaging, AI architecture, and efficient
-
measure success. Basic Qualifications: A PhD in Materials Science and Engineering or a related field completed within the last 5 years Preferred Qualifications: Strong background in computational and image
-
). NCCS operates the Frontier exascale supercomputer and world-class data facilities. This role sits at the intersection of AI at scale and HPC, giving you unmatched resources to prototype new ideas, run
-
twins are leveraged to develop paradigm shifts in quality assurance, quality control, real-time process control, and design optimization for the United States. In this digital environment, you will use
-
computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
-
skills. Special Requirements: Postdocs: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting
-
Sciences Division (CSD), Physical Sciences Directorate, at Oak Ridge National Laboratory (ORNL). The postdoc will perform molecular dynamics simulations, statistical mechanics (e.g., rate theory) and
-
. Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs. Special Requirements: Postdocs: Applicants
-
across the laboratory. Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs. Postdocs: Applicants
-
, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy