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the last five years. A minimum of 3 years of experience in (a) design and operation of experimental thermal/fluid systems, (b) mechanical systems and instrumentation, (c) fluid dynamics, combustion, and heat
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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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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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Requisition Id 16715 Overview: We are seeking a Postdoctoral Research Associate who will use multiscale modeling and simulation to develop probabilistic lifing frameworks for high-temperature alloys
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researcher to join the Workflow Systems Group and help advance the use of AI in scientific discovery. This position centers on scientific machine learning, automated AI/ML optimization, and high-performance
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properties as well as test and develop novel high performance computing methods for first principles materials calculations. The successful candidate will be mentored and teamed with staff in the National
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industrial heat pumps). The role also involves research and analysis of technologies and practices for increasing the energy efficiency of the industrial sectors. The primary objective is to deliver the direct
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avoidance, autonomous exploration, frontier selection, and localization-aware trajectory planning. Develop high accuracy point cloud registration and mapping workflows. Plan and conduct experiments
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processing (e.g., arc melting, heat treatment) and relate processing to performance. Apply analytical and modeling approaches to interpret experimental results. Collaborate with internal and external research
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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