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systems, including GPU-accelerated platforms. Develop and maintain scientific software, primarily in Python, using modern practices for software development, testing, documentation, and version control
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. Evaluate impacts on energy efficiency, mobility, reliability, and resilience at the vehicle, corridor, and network levels. Produce reusable research software, datasets, models, evaluation tools, and
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problems, and you will apply your work in multidisciplinary domains alongside globally recognized experts. You will bring creative thinking, teamwork, and hardware-software co-design skills to bear as you
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. This researcher will focus on advancing secure, trustworthy, and efficient AI solutions for scientific applications by developing state-of-the-art sparse algorithms in matrices, tensors, and networks
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Confidential Computing and Secure Multi-tenancy. The candidate will be able to make research contributions in areas of system software architectures to support secure computing enclaves on large scale HPC and
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interact closely with industry partners. These engagements will play a vital role in ensuring success of programs and the adoption by project sponsors, and in developing your network across academia and
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analytical and modeling approaches to interpret experimental results. Collaborate with internal and external research teams to define and advance research directions. Present research findings and publish
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simulation tasks. Develop and maintain HPC-ready software workflows for distributed training, large-scale inference, scalable data ingestion, and data management on leadership-class computing systems and
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computing. Redesign of storage systems to meet evolving demands in AI/ML and edge-to-HPC workflows, including support for data movement, retention policies, and user-defined storage behaviors. Major Duties
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loads, transmission networks, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component/device models into open-source software tools for integrated