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of integrated data and AI workflows that span data acquisition, modeling, and decision-making, including deployment at the edge and across distributed systems. You will have access to extensive experimental and
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interacting teams of researchers. Special Requirements: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before
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massively parallel algorithms and code performance profiling are a plus. Special Requirements: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must
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., difference-in-differences). Contributions to reports, presentations, and peer-reviewed journal articles. Collaborate with ORNL scientists involved in these efforts, to gain expertise in the economic analysis
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to support data-driven design decisions and performance tuning. Explore trade-offs in DDR and HBM usage patterns, and propose architectural improvements for mixed-memory and bandwidth-intensive workloads
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to ever changing needs. Special Requirements: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting
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marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws. For foreign national candidates: If you have not resided in the U.S. for three consecutive
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candidate will have the opportunity to assist ORNL scientists involved in these efforts, to gain expertise in biokinetic and dosimetric modeling, and to assist and eventually lead in the preparation of open
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architectural design decisions for massively parallel heterogeneous systems, including pathways that integrate quantum or analog co-processors. Performance Engineering at Scale: Profile, model, and optimize
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environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs. Special Requirements: Applicants cannot have received their Ph.D. more than five years prior