60 postdoc-artificial-intelligence Postdoctoral positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment. Postdocs: Applicants cannot have received
-
Postdoctoral Research Associate in the areas Artificial Intelligence (AI) for Integrated Hydrology Modeling. The successful candidate will have a strong background in computational science, data analysis, and
-
Sciences Directorate, at Oak Ridge National Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) and machine learning/artificial
-
applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and
-
. Intelligent Sampling for Federated Learning: Investigating frameworks (such as SICKLE) for intelligently sampling cross-facility extreme-scale data to enhance federated learning workflows with platforms like
-
-year residency requirement, you will be required to obtain a PIV credential to maintain employment. Postdocs: Applicants cannot have received their Ph.D. more than five years prior to the date
-
computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
-
in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
-
applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and
-
capabilities in a wide range of areas, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data