Explainable AI - Postdoctoral Researcher

Explainable AI - Postdoctoral Researcher

Mid-Senior Level | Full-time
Postdoctoral/Fellowship | Livermore, CA | 08/12/2026
Reference #: REF
8682W
Job Code: PDS.
1 Post-Dr Research Staff 1
Organization: Computing
Position Type: Post Doctoral
Security Clearance: None/Position does not require US citizenship (assignments longer than 179 days require a federal background investigation)
Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
Medical Exam: Not applicable

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

We have an opening for a Postdoctoral Researcher in Explainable AI to contribute to fundamental R&D on understanding what modern AI models learn and how that knowledge is represented internally. As foundation models and deep surrogates inform consequential scientific and national security decisions, domain experts need to inspect, validate, and steer model internals, making interpretability as much a human-AI collaboration problem as a modeling one.

Your work will focus on recovering human-meaningful structure from learned representations, including sparse decompositions of activations, concept discovery, mechanistic analysis, and causal intervention, and on the interactive interfaces and evaluation methodology that let experts interrogate that structure and the given explanations. Applications area includes but not limited to multimodal

SciMLmodels and deep surrogates for various simulations. This position will be in the Machine Intelligence Group in the Center for Applied Scientific Computing (CASC) Division within the LLNL Computing Directorate.

This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home one or more days per week.

• Develop and evaluate methods for interpreting the internal representations of deep models, including sparse decompositions of activations, concept extraction, and representation steering.
• Design human-in-the-loop workflows that let domain experts explore, validate, and correct discovered concepts, and evaluate those workflows with real users.
• Establish rigorous evaluation methodology for interpretability claims, i.e., faithfulness, stability, and causal grounding.
• Research, design, implement, and apply advanced machine learning methods for multiple applications in a collaborative scientific environment.
• Conduct cutting-edge machine learning research effectively and independently.
• Actively participate with project scientists and engineers in defining, planning, and formulating experimental, modeling, and simulation efforts for complex problems stemming from national security applications.
• Propose and implement advanced analysis methodologies, collect and analyze data, and document results in technical reports and peer-reviewed publications.
• Contribute to grant proposals and collaborate with others in a multidisciplinary team environment, including academic and industrial partners, to accomplish research goals.
• Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
• Perform other duties as assigned.

• Recent Ph.D. in…