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computer science or a related discipline. Good knowledge of agentic AI/AI workflows, parallel computing, algorithms, and system performance analysis and optimization. Proficiency in programming languages
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Sciences (NCCS), Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL) to perform leading-edge computational materials research and development. The scientific
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environments, and high-performance or parallel computing is desirable. The candidate will also prepare technical documentation, reports, peer-reviewed publications, and presentations and collaborate
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, and reproducible code development skills; distributed or parallel computing is a plus. Experience designing and executing field experiments in urban or environmental settings, with willingness to
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, dynamic-link libraries, SQL, Git or other version-control systems, Linux, high-performance computing, parallel computing, or automated testing Experience with watershed processes, groundwater-surface
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analysis. Our state-of-the-art parallel-computing environment includes numerous large-scale clusters and other specialized computing systems. Posting Duration: This posting will be open for application
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and parallel computing, or scientific simulation; Effective oral and written communication skills; Ability to work well independently as well as in a collaborative team environment. COMPENSATION AND
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learning, high-performance and parallel computing, or scientific simulation; Effective oral and written communication skills; Ability to work well independently as well as in a collaborative team
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Requirements Demonstrated expertise in software and algorithm development, computational methods, data analysis, modeling, machine learning, high-performance and parallel computing, or scientific
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The University of Texas MD Anderson Cancer Center | Houston, Texas | United States | about 9 hours ago
computational biology, physics and (bio)statistics, biology or medicine. Applicants must have a proven publication record. Prior experience with handling massively parallel sequencing data is considered an