151 parallel-computing-numerical-methods "Institute of Computer Science" research jobs at Oak Ridge National Laboratory
Sort by
Refine Your Search
-
Listed
-
Program
-
Field
-
numerical discretization techniques, high performance computing, mesh generation, and geometry representation for a wide variety of physics applications. Our intention is to integrate computational
-
mixed-precision, energy-efficient, and accelerator-optimized methods — for large-scale numerical, scientific, and/or AI models. Demonstrating the scalability of new algorithms on leadership
-
intersection of applied mathematics, computational science, and high-performance computing. The successful candidate will help develop advanced scientific computing methods and deploy them on state-of-the-art
-
/or tools such as Parallel, Flux or Parsl . Familiarity with concepts of parallelism, scalability, and efficient utilization of computational resources. Experience with GPU accelerators and computing
-
how to use the software. Solid understanding of neuromorphic computing and SNNs, including common neuron models (e.g., leaky integrate-and-fire) and SNN training or conversion methods (e.g., spike
-
Requisition Id 17131 Overview: Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative
-
Requisition Id 17131 Overview: Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative
-
Requisition Id 17212 Overview: As a research staff member, you will conduct and lead research at the intersection of high performance computing, artificial intelligence, and neuromorphic computing
-
Qualifications: PhD. in computer science, computer engineering, electrical engineering, computational science, or a closely related field. 8 or more years of relevant research experience beyond the
-
numerical methods, high-performance computing (HPC), or large-scale data analysis. Experience in applying AI/ML techniques to hydrological and Earth sciences. Proficiency in scientific programming