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. In addition, you will develop and leverage training data sets derived from years of ARM metadata records, as well as design and implement Large Language Model (LLM)-based conversational interfaces
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computational mesh generation. In this role, you will apply your software engineering skills to develop and validate computational results that support large-scale, physics-based simulations across a variety of
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compliance-driven or DOE-regulated environments. Facility with AI and large language models (LLM) tools to support analysis, documentation, reporting, and knowledge integration, consistent with data security
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/Output Controllers (IOCs), Operator Interfaces (OPIs) and networking. Maintain EPICS services, including data archiving, alarming, and gateway services; monitor performance and plan upgrades as needed
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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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comparative research across Mojo, Julia, Rust, and vendor toolchains. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, or related field. Experience with LLMs or agentic AI frameworks
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. Examples of subcontracting efforts the candidate will manage are leading competitions for large first-of-a-kind equipment purchases, professional and consulting services, etc. This position resides in
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with developing AI/ML workflows and integrating them into software projects. Developing or contributing to large, complex software systems. Scientific data visualization and/or scientific data analysis
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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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: The design and analysis of computational methods that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance