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scientific outputs that may include peer-reviewed publications in top-tier water journals, professional scientific code/software contributions, and high-quality datasets. Candidates must also be willing
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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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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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and able to participate creatively in defining and refining research directions. Major Duties/Responsibilities The successful candidate will interact with a team of scientists and engineers at ORNL in a
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analysis software. The prospective candidate will also have the opportunity to develop their own science that will complement the proposed DIB studies. Major Duties/Responsibilities: Study droplet interface
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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating
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advanced computational approaches, software engineering, high-performance computing, and an understanding of materials science, with an emphasis on metallurgy related to phase transformations and/or
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: Experience in one more of the following areas: Mathematical tools for data analysis Numerical methods for differential and integral equations Modern machine learning software tools and frameworks
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research spanning detector simulation, Spiking Neural Network (SNN) design, neuromorphic hardware, and data-rich experimental systems such as CMS pixel detectors, Timepix4, and novel photodetector
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experiments in the SNS ring including experiment design, and data analysis. Develop software for data acquisition and analysis as needed. Perform simulations using a well-tested model of the SNS ring to