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, and material characterization efforts Supervise students and interns supporting modeling and data analysis tasks Prepare technical reports, invention disclosures, and peer-reviewed publications Present
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within the last 5 years Preferred Qualifications: Experience in one more of the following areas: Mathematical tools for data analysis Numerical methods for differential and integral equations Modern
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through model–experiment validation workflows. Develop and implement advanced data analysis methodologies, automated processing tools, and reproducible workflows to generate validated, publication-quality
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and clustered computing services to researchers who process large data sets and/or develop code as a part of their project. Ensure the availability, performance, scalability, and security of production
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applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature
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. Architect end-to-end experimental workflows that integrate instrument control, data acquisition, processing, storage, and analysis. Develop automated and semi-autonomous measurement pipelines enabling high
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discipline). Strong programming or computational skills (e.g., Python, MATLAB, or similar) sufficient to support modeling and data analysis. Familiarity with manufacturing processes, materials processing
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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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Requisition Id 15723 Overview: The Manufacturing Energy Efficiency Research & Analysis (MEERA) Group within the Manufacturing Science Division (MSD) at the Oak Ridge National Laboratory (ORNL) is