Nuclear Data Scientist

At Idaho National Laboratory (INL), you will help advance the Genesis Mission—a strategic collaboration between INL and the U.S. Department of Energy to accelerate the application of artificial intelligence, advanced computing, and scientific innovation to solve the nation's most complex energy, national security, and critical infrastructure challenges. As part of a multidisciplinary research team, you will analyze complex data and develop innovative computational solutions across cloud, on-premises, and edge computing environments.

You will apply emerging technologies, including explainable artificial intelligence (XAI), large language models (LLMs), retrieval-augmented generation (RAG), and physics-informed machine learning to support cutting-edge research and mission objectives. This role includes developing advanced software solutions, visualization tools, and scalable analytics while collaborating with scientists, engineers, government agencies, academia, and industry partners to deliver impactful research outcomes. Successful candidates will contribute to technical publications, strengthen INL's leadership in AI-enabled scientific discovery, and support DOE's vision for the future of national laboratory research through the Genesis initiative.

• Contribute to the DOE-INL Genesis initiative by developing innovative AI, machine learning, and advanced computing capabilities that accelerate scientific discovery and enable transformational solutions for national energy, security, and critical infrastructure challenges.
• Analyze complex data and generate actionable insights in response to data analytics, visualization, modeling, and simulation needs across cloud, on-premises, and edge-based computational environments.
• Design, develop, and apply advanced technologies including Explainable Artificial Intelligence (XAI), Machine Learning (ML), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), physics-informed machine learning, systems performance analysis, and data sensor fusion methodologies.
• Collaborate with multidisciplinary teams of scientists, engineers, software developers, and subject matter experts to solve complex research and engineering problems.
• Partner with DOE sponsors, other national laboratories, government agencies, universities, and industry collaborators to advance research objectives and deliver mission-focused solutions.
• Publish research findings in peer-reviewed journals, technical reports, and conference proceedings while contributing to INL's national leadership in AI-enabled research.
• Support the development and execution of cross-cutting technical programs that address strategic priorities for multiple DOE and federal customers.
• Develop, test, deploy, and maintain research software, data processing pipelines, notebooks, and applications supporting scientific computing and data analytics.
• Design and implement custom software solutions, including 3D visualization tools, parallel computing applications, batch automation, web APIs, and scalable data services.
• Collaborate with software engineers and database developers to develop, test, and deploy software across development, staging, and production environments using modern software engineering practices.
• Evaluate data quality, identify and communicate data integrity issues, and develop repeatable data processing workflows that ensure accurate and reliable analyses.
• Work closely with domain experts to understand scientific questions, identify critical data features, develop analytical methodologies, and design meaningful performance metrics that characterize complex system behavior.
• Apply state-of-the-art data science, AI, modeling, and computational techniques to support INL's mission of ensuring the nation's safe, secure, resilient, and sustainable use of engineered systems.
• Follow INL software engineering standards, cybersecurity requirements, configuration management practices, and policies governing sensitive information and research data.
• Collaborate with data providers, database administrators, and software developers to rapidly diagnose and resolve data, infrastructure, and software issues.

• Levels 2:
  Master's degree in Data Science, Computer Science, Engineering, Mathematics, Physics, Artificial Intelligence, Autonomy, or a closely related technical discipline with 0 years of relevant experience.
• Level 3:
  Master's degree in Data Science, Computer Science, Engineering, Mathematics, Physics, Artificial Intelligence, Autonomy, or a closely related technical discipline and 2 or more years of relevant experience; or a Ph.D. in one of the above disciplines and 2 or more years of relevant experience.
• Experience in data science, data analysis, and software development using Python, C#, Java, or C++.
• Experience developing AI-enabled applications, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and Python/Git Hub collaborative development…