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- 
                Field
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                lead technician working with the life safety services. Maintains comprehensive records utilizing computer programs for all building alarm checks, supervisory panel checks, and alarm tests. Maintains 
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                to cutting-edge research aimed at transforming scientific data management and workflows to enable AI-readiness at scale. You will work on designing system software for automating processes such as intelligent 
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                , the Stanford CS Department has influenced society at levels that remain without parallel among academic institutions. Its spin-offs are among the most successful corporate ventures in the world, and many 
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                workflows to enable AI-readiness at scale. You will work on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed 
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                leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration 
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                developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation of results. Deliver ORNL’s mission by aligning 
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                , and 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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                parallel/multiplexed assays, etc.) is desirable. Ability to interpret and discuss experiments and critically contribute to writing of manuscripts and grant proposals is expected. Well-organized, able 
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                working with one or more front end frameworks like React, Vue, and Angular Ability to work on multiple different projects in parallel Skilled in, or strong interest in learning, data visualization tools and 
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                -driven techniques for the generation and exploration of complex, large-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel