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ORNL, other national laboratories, and the hydropower stakeholder community at-large to create data, products, and tools for hydropower licensing Find, extract, and analyze data from governmental
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health research projects. The research activities include HIPAA compliant research data that has been entrusted to ORNL by sponsors such as the National Cancer Institute. We work on some of the most
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software systems to manage and process large datasets related to building energy modeling and data visualization Strong software development skills for automation of many knowledge-based tasks in a version
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bottlenecks, and develop strategies for improving computational efficiency. Work effectively individually and within a team to engineer large multi-component scientific and data-intensive software to meet the
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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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service offerings (e.g., large-scale geospatial compute pipelines, data ingest/curation/archive, analytics/visualization, user support). Establish operating policies, SLAs, user workflows, resource
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, supported by: Multiscale modeling (material (molecular) → process → manufacturing (scale up)) Data-informed experimentation Selective use of AI/ML and big-data techniques where they add real value
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version control, CI/CD, testing frameworks, configuration management, and scalable computing architectures. Familiarity with high-performance computing (HPC), data management workflows, or large-scale data
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. Experience working with large environmental datasets such as flux tower and remote sensing data. Skills in statistically based model evaluation using observational data. Evidence of leadership potential
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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A BS in computer science, data science, artificial intelligence, business analytics management