39 high-performance-computing Postdoctoral positions at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
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
-
crystal material’s growth and characterization. You will perform cutting-edge research on theory and modeling of dynamics in condensed matter. Major Duties/Responsibilities: Development of theoretical
-
, dimensionality reduction, embeddings, etc.). Understanding of computational scaling techniques for machine learning and high-performance computing. Preferred Qualifications: Expertise in foundational models 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
-
transformative solutions to compelling problems in energy and security. We are seeking a Postdoctoral Research Associate to perform experimental studies on chirality driven quantum states. This position resides in
-
, high-performance computing (HPC), and computational sciences. Major Duties/Responsibilities: Participate in: (1) design and implementation of scalable DL algorithms for atomistic materials modeling
-
, high performance computing and deep learning. The candidate will work in a collaborative research and development environment focusing on designing, implementing, and applying robust and high performance
-
Directorate (PSD) at Oak Ridge National Laboratory (ORNL). This position offers an exciting opportunity to contribute to research in nuclear theory using high-performance computing and advanced many-body
-
). Knowledge of high-performance computing or cloud environments for large-scale data. Strong collaboration skills and ability to work in interdisciplinary teams. Special Requirements: Applicants cannot have