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Requisition Id 15603 Overview: The National Center for Computational Sciences (NCCS) at the Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral research associate in the area of HPC
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system
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systems (Mojo, Julia, Rust, Python), and HPC system co‑design. This position is embedded within the larger DOE ASCR ecosystem, with direct relevance to ongoing efforts, and related AI‑for‑HPC thrusts
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the tensor network simulations using HPC resources for selected case studies. Analyze simulated data and compare directly with RIXS experimental spectra; assist in data interpretation and (if applicable
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• Execute large-scale simulations on CPU and GPU-based HPC clusters • Analyze results, generate technical reports, and deliver project outcomes on schedule • Prepare scientific reports and publish in
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for unstructured meshes and/or finite element methods. Experience with CFD discretization techniques for unstructured meshes and/or finite elements with an emphasis on highly scalable algorithms for exascale HPC
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours ago
++, or similar. Preferred Qualifications, Competencies, and Experience Preferred qualifications include experience with molecular dynamics or atomistic simulations, supercomputing or HPC environments, scientific
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. Strong experience developing, deploying, and optimizing applications and workflows in high-performance computing (HPC) environments. Demonstrated programming proficiency in C/C++ (preferred) and Python
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the data from HEP experiments is strongly required Programming expertise in Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability
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. Experience working with a high-performance computing (HPC) environment. Familiarity with machine learning and advanced statistics. Experience with analysis of time series data from intracranial EEG (iEEG