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at the Argonne campus in Lemont, Illinois, five days per week. Preferred qualifications: Experience with MOOSE. Experience with PyTorch. Experience with HPC job scheduling systems. Job Family Postdoctoral Job
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. The ANL ATLAS group maintains strong involvement across the experiment, including detector operations, TDAQ upgrades, Software and Computing, ML development, and High-Performance Computing (HPC
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Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork
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(HPC) environments and large-scale data management. Experience with version control (e.g., Git) and collaborative software development practices. Experience with real-time analysis and instrument control
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multidisciplinary team of scientists and High Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state
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math, HPC, signal processing, computational physics and materials science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of
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modeling. Perform predictive modeling using high-performance computing (HPC) infrastructure. Validate computational predictions by collaborating with experimental groups conducting reverse genetics studies
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of scientists and High-Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state
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engineering team to translate the models into production. The successful candidate will be part of a cross-lab, highly inter-disciplinary team of experts in ML, applied math, HPC, signal processing
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct