Senior Super Intelligence Computational Scientist

Idaho National Laboratory • Idaho Falls, ID

3d • Remote

About The Position

Idaho National Laboratory’s Scientific Computing and Artificial Intelligence (SCAI) division in NS&T is hiring a Senior Computational Scientist for its Multiphysics Computational Frameworks department. The role designs, implements, documents, and supports MOOSE (the Multiphysics Object Oriented Simulation Environment), an open-source framework for high-fidelity modeling of real physical systems. MOOSE supports work in nuclear science, environmental science, and other fields, with international collaborators in the US, Europe, and Australia.

The position strengthens MOOSE and develops super-intelligence (SI) agentic workflows that combine MOOSE with modern SI and machine-learning methods to accelerate nuclear energy design and licensing. Work includes improving parallel performance and accelerator support, generating synthetic data for surrogate models, and integrating those models into SI-driven analysis and design workflows. The role also represents the department in external partnerships, shapes shared technical direction, produces technical and research materials, and develops program opportunities. Candidates at this level are expected to shape technical direction.

This is a multi-level posting, with placement at Level 4 or Level 5 based on the depth and breadth of demonstrated experience and skills. The position is subject to Department of Energy export-control restrictions; applicants must be US citizens or US Green Card holders. The team works a 9x80 schedule, with every other Friday off. The position is based at the Collaborative Computing Center in Idaho Falls or may be remote.

Requirements

• Level 4: Master’s degree in nuclear science, materials science, computational engineering, computational applied mechanics, computer science, engineering, physics, mathematics, or a similar field, plus 6 years of relevant experience; or a PhD in one of those fields or a similar field, plus 4 years of relevant experience.
• Level 5: Master’s degree in nuclear science, materials science, computational engineering, computational applied mechanics, computer science, engineering, physics, mathematics, or a similar field, plus 8 years of relevant experience; or a PhD in one of those fields or a similar field, plus 6 years of relevant experience.
• Proficiency in C++ and Python.
• Experience with object-oriented programming, finite-element methods, advanced numerical methods for nonlinear analysis, and development of complex engineering analysis software.
• Demonstrated experience in parallel computing and hardware accelerator technologies, such as GPUs, applied to large-scale scientific software.
• Experience with Large Language Models for designing agents, connecting agents to tools using modern protocols such as MCP, and other SI agents using the A2A protocol.
• Must be a US citizen or US Green Card holder due to Department of Energy export-control restrictions.
• Ability to perform the described physical duties, with reasonable accommodations where applicable.

Nice To Haves

• Demonstrated leadership executing large, complex, multidisciplinary programs across multiple organizations.
• Deep skill in one or more of parallel computing, nonlinear solvers, preconditioning, applying SI to scientific software applications, or developing complex scientific software for partial differential equations using finite-element or finite-volume methods.
• Hands-on experience in physics, applied mathematics, machine learning, super intelligence, or data science; surrogate modeling; and SI-driven workflows.
• Experience with software verification and validation and a record of peer-reviewed research accomplishments.

Responsibilities

• Design, implement, document, and support new MOOSE framework capabilities, including numerical methods and multiphysics coupling.
• Build SI agentic workflows that combine MOOSE with modern SI and machine-learning methods to accelerate nuclear energy design and licensing.
• Optimize parallel performance and use hardware accelerator technologies such as GPUs for large-scale simulations and SI workflows.
• Generate synthetic data at scale to train surrogate models and integrate those models into SI-driven analysis and design workflows.
• Represent the department and develop partnerships with DOE, other national laboratories, industry, academia, and international collaborators; negotiate and shape shared technical directions.
• Author technical reports, peer-reviewed publications, proposals, and presentations.
• Identify and develop new program opportunities for the team.
• Shape technical direction for the team and its work.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior