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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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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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, enabling manual and automated adversarial testing at scale. Build and integrate AI-on-AI testing infrastructures, where AI models can actively challenge each other in adversarial contexts to detect
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for the section; support the Group Leaders build upon their existing research portfolio and to ensure their success and the success of the R&D groups as world-recognized leaders in their fields; ensure that staff
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development, fostering a safe and inclusive work environment, and maintaining focus on priority tasks. Build and sustain world-class technical expertise within the group by recruiting top talent, fostering
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modeling techniques and make fundamental contributions to the field. Interact with other researchers, technicians, and students to shape and drive the research agenda. Present and report research results and
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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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challenges facing the nation. We invite applications for a Principal Engineer for Geospatial Computing Infrastructure. This dynamic and visionary leader will launch and build a next-generation Geospatial Data
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the division’s, directorate’s, and laboratory’s research plans and investments. Build strong teams by collaborating across ORNL and securing external expertise when needed. Leverage ORNL facilities and resources
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, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut-science outcomes. The candidate will be a research and development staff within the Multiscale