17 high-performance-computing "Multiple" Postdoctoral positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
our growing research team. These positions focus on developing next-generation AI and high-performance computing (HPC) methods for computational imaging and spatiotemporal data analysis. We
-
in high-performance computing and data analytics with applications in a large variety of science domains and NCCS is home to some of the fastest supercomputers and storage systems in the world
-
Requisition Id 15823 Overview: We are seeking a postdoctoral researcher skilled in biogeochemistry who will contribute to mercury remediation technology development program, specifically focusing
-
Research Associate to develop and apply computational technique for advanced manufacturing using high-performance computing resources. ORNL’s CCP conduct world-leading research and development in multi-scale
-
advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms
-
/Responsibilities: Developing and validating high fidelity whole building energy modeling Performing experiments in a test facility and experimental data analysis Developing and deploying AI based advanced control
-
post-doctoral research associate to simulate amorphous materials and crystallization reactions using atomic-scale simulations. As a post-doc, you will utilize high performance computing and rare event
-
of high-performance computing and its applications. An excellent record of productive and creative research, as demonstrated by publications in top peer-reviewed journals. Strong problem-solving skills and
-
-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency and reliability of scientific discovery
-
, high-performance computing (HPC), and computational sciences. Major Duties/Responsibilities: Participate in: (1) design and implementation of scalable DL algorithms for atomistic materials modeling