Watch Video: Software at ORNL 

Software underpins many of the scientific discoveries made by ORNL. Our goal is to ensure that the software we create embodies the best practices available to maximize the reliability and efficiency of scientific research to increase credibility and accelerate discovery.– *Gregory Watson, Group Leader, Application Engineering*

## Software Resources

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A hub for open source projects.

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Software for science

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Software repositories 

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External facing Gitlab server for users with both UCAMS and XCAMS accounts.

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## Software and Data Expo

Learn more about ORNL's annual showcase of scientific software.

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## News and Careers

Software news

Careers at ORNL

## Expertise

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Engineering the next generation of high-quality scientific software.

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Delivering advanced scientific applications with best-in-class methods, design, and implementation.

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Developing operationally-critical custom software services for the NCCS.

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A premier research institution for supercomputing, data science, and geographic information systems.

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Partnering with HPC and data analytics users on algorithmic and performance improvements and characterizes application performance and application requirements.

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Develops, maintains, and manages innovative software systems that support missions of the National Nuclear Security Administration.

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Leads application-driven development of innovative and validated computational tools and analysis methods to efficiently model fission energy systems, nuclide transmutation, and nuclear fuel cycles.

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Experts in Scientific Domains and Computation.

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Designs, develops, deploys and analyzes advanced machine learning and decision science algorithms and techniques for energy applications.

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Offers scientific, technical, operational, and thought leadership by developing, hardening, and deploying solutions for compute and data intensive computing environments.

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Conducts advanced research, design and development of algorithms and systems employing computational sensing approaches with Images and signals.

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Creating new machine tools and developing new manufacturing techniques for machining processes using conventional and hybrid processes. 

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Optimizing data applications and systems for advanced platforms to accelerate discovery.

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Engineering systems for data capture, analysis, and sharing.

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Providing software expertise to develop IoT solutions in manufacturing.

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