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to bring strong expertise in scalable deep learning, high-performance computing (HPC), scalable data management, Linux environments, and production-quality scripting for HPC workflows. Major Duties
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. Demonstrated programming ability and knowledge of Python and/or C++. Experience with deep learning frameworks like PyTorch and application on high-performance computing (HPC) environments using distributed data
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-loop” optimization environments, enabling AI agents to analyze, transform, and validate IR with performance-driven reasoning. HPC System Co‑Design: Investigate methods through which AI agents guide
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(HPC), or large-scale data analysis. Experience in applying AI/ML techniques to hydrological and Earth sciences. Proficiency in scientific programming languages such as Python, Julia, R, Fortran, or C/C
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-Performance Computing (HPC), scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature strengths in high-performance computing
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multi-physics simulations on high performance computing (HPC) and ML Experience working in a multi-disciplinary research environment Special Requirements: Applicants cannot have received their Ph.D
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professionals to accelerate scientific discovery and engineering advances across a broad range of disciplines. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division
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system) and disordered materials is also desirable. The project will involve developing autonomous materials discovery workflows on HPC platforms that can learn structure-chemistry-property relationship in
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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of NTI and CNMS to develop HPC workflows that can perform multi-fidelity simulations to predict and interpret a wide range of structural and electronic characterization techniques Develop physics-informed