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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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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/scalable
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-reviewed journals and conferences Demonstrated research experience with HPC, AI/ML and/or distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as
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distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and parallel computing. Demonstrated hands-on experience and
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Department of Veterans Affairs (VA). As such, you will have the opportunity to work on some of the most challenging and impactful research and development programs in healthcare informatics, bioinformatics
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applications. You’ll help design, train, and evaluate AI systems that plan, reason, and take actions to accelerate scientific discovery across domains (materials, chemistry, climate, fusion, biology, and more
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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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packaging, with the aim of reestablishing U.S. prominence in semiconductor manufacturing. With over $1 billion in funding from the US DoD and the state of Texas, we’re at the forefront of creating cutting
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develop a prototype ocean analysis-forecast system for the U.S. east coast extending from the Gulf of Maine to the Caribbean Sea. The resulting East Coast Community Ocean Forecast System (ECCOFS) will
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, Bioinformatics, Computer Science, Mathematics, Statistics, Data Mining, Parallel Programming, Supercomputing, or Cloud Computing. 3) Experience collaborating with diverse and geographically distant teams