43 parallel-"Computer-Vision-Center" "Computer Vision Center" positions at Oak Ridge National Laboratory
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management, parallel computing, and performance optimization while helping evaluate and introduce emerging technologies that advance mission capabilities. You will work alongside a multidisciplinary team of
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parallel computing, with a proven ability to work within highly secure and regulated environments. This role involves close collaboration with security teams, scientists, and IT leadership to ensure
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, including pretrained universal models and models tailored to specific chemical and materials systems. Develop, debug, profile, and optimize scientific codes and workflows on massively parallel computing
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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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are looking for candidates with extensive experience in HPC architecture, cluster management, and parallel computing, with a proven ability to work within highly secure and regulated environments
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management, parallel computing, and performance optimization while helping evaluate and introduce emerging technologies that advance mission capabilities. You will work alongside a multidisciplinary team of
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the following areas is preferred, and an exceptionally strong candidate in a single area is also encouraged to apply. Relevant areas include: Parallel and distributed graph and or ML algorithms
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architectural design decisions for massively parallel heterogeneous systems, including pathways that integrate quantum or analog co-processors. Performance Engineering at Scale: Profile, model, and optimize
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experience in HPC architecture, cluster management, and parallel computing, with a proven ability to work within highly secure and regulated environments. This role involves close collaboration with security
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Python and C or C++. Experience with parallel and distributed computing using technologies such as MPI, distributed machine-learning frameworks, and HPC workload managers. Experience using GPU-accelerated