71 parallel-computing-numerical-methods Postdoctoral research jobs at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
research and development in the areas of gauge field generation, linear and eigen-solvers, or novel analysis methods. This position will reside in the Advanced Computing for Nuclear, Particle and
-
HPC research within past five years. Preferred Qualifications: The ability to work independently and develop and deploy methods at scale. Experience in high-performance computing and software
-
Requisition Id 16562 Overview: The Analytics and AI Methods at Scale (AAIMS) group at the National Center of Computational Science (NCCS) at the Oak Ridge National Laboratory (ORNL) is seeking
-
candidate will join the Multiscale Materials (MsM) group within the Advanced Computing Methods for Physical Sciences Section in CSED. The MsM group is dedicated to delivering multiscale, multi-fidelity
-
methods. Additionally, you will develop/refine finite element and numerical analysis models to portray shear strength response as a function of temperature, and to attempt to ultimately reconcile those
-
experience in hydrological or Earth system modeling, with emphasis on process understanding and prediction. Strong background in computational sciences, including numerical methods, high-performance computing
-
Computing Methods for Physical Sciences Section in CSED. The MsM group is focused on delivering multiscale, multi-fidelity computational models and systems using algorithms and analytics for materials and
-
. Experience with heterogeneous and parallel computing technologies, programming models, or accelerators, including CPUs, GPUs, FPGAs, and emerging computing technologies. Familiarity with quantum software
-
Requisition Id 16505 Overview: The Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking an exceptional Postdoctoral Researcher to advance programming systems
-
well as experience with HPC environments and parallel computing. Demonstrated hands-on experience and understanding of developing scientific data management, workflows and resource management problems. Strong problem