Nuclear Data Scientist

Idaho National Laboratory (INL) is a science-based, applied engineering national laboratory dedicated to supporting the U.S. Department of Energy's mission in nuclear energy research, science, and national defense. They are seeking a Nuclear Data Scientist to advance the Genesis Mission by analyzing complex data and developing innovative computational solutions in AI and machine learning to address national energy and security challenges.

What you'll do:

• 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

What they're looking for:

• 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/GitHub collaborative development environments
• Ability to obtain and maintain a DOE level “Q” security clearance, which requires US Citizenship
• Cloud computing platforms and cloud-native analytics (AWS, Microsoft Azure, Google Cloud Platform, or similar)
• Scientific computing frameworks such as SciPy, NumPy, Jupyter Notebook, PyTorch, TensorFlow, CUDA, and related AI/ML libraries
• Natural language processing, graph databases, knowledge graphs, vector databases, and modern data management architectures
• High-performance computing (HPC), distributed computing, and parallel programming
• AI model evaluation, explain ability techniques, and physics-informed machine learning
• Research software development supporting scientific computing and advanced data analytics
• Developing solutions that support DOE mission areas, including energy systems, nuclear science, critical infrastructure, cybersecurity, or national security research

Benefits:

• Medical, Dental, Vision, and Flexible Spending Accounts
• 401(k) with a 4.2% employer contribution and up to 4.8% match (regular positions) or self-contribute access (postdoctoral positions)
• Paid time off (personal leave)
• Employee Education Program (tuition assistance for eligible positions)
• Comprehensive Relocation Package