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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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and/or 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
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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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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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-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
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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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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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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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parallel programming. ● Experience with writing scientific articles. ● Experience with writing scientific machine learning. Overtime Status Exempt: Not eligible for overtime Appointment Type Restricted
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 2 months ago
; strong physical, mathematical, and computational background; experience with programming in at least one general-purpose language (preferably Julia) and parallel computing; demonstrated effective written