Postdoctoral Research Associate - AI Lab Operations

As a postdoctoral researcher, you will help solve some of the most challenging problems the world faces. You will perform impactful research on a range of significant problems, and you will apply your work in multidisciplinary domains alongside globally recognized experts. You will bring creative thinking, teamwork, and hardware-software co-design skills to bear as you develop new methods to address scientific and engineering problems, collaborate with leaders in your field and across the laboratory, and disseminate innovative results through publications and presentations.

The Learning Systems Group in the Computer Science and Mathematics Division (CSMD) at Oak Ridge National Laboratory (ORNL) seeks a highly motivated Postdoctoral Research Associate to lead research at the frontier of Generative AI, Large Language Models (LLMs), and Human-in-the-Loop Agentic AI systems. This role directly targets critical DOE Operations problems by advancing AI-driven tools for real-world operational safety, predictive maintenance, automated hazard identification, and proactive risk mitigation  successful candidate will develop, fine-tune, and evaluate advanced generative AI architectures, multi-agent orchestrations, and specialized operations software tools to analyze unstructured operational data, forecast hazardous conditions, and support human decision-making in high-consequence operational environments.

The candidate will collaborate closely with machine learning researchers, software developers, and domain safety experts across CSMD and lab operations teams. Research directions emphasize practical operations tool development, AI-driven risk modeling, multi-agent AI workflows for incident prevention, and trusted RAG systems for safety compliance and real-time hazard evaluation. The position offers access to large-scale GPU computing resources, opportunities to publish in top AI and safety engineering venues, and the chance to deploy impactful AI solutions for national laboratory and DOE operational safety challenges.

• Conduct original research and software tool development in Generative AI for operational safety, focusing on solving complex DOE operations problems through intelligent hazard identification, incident trend analysis, and predictive risk mitigation.
• Architect, fine-tune, and deploy multi-agent AI systems, instruction-tuned LLMs, and Retrieval-Augmented Generation (RAG) pipelines to build specialized AI operations tools for automated risk scoring, real-world hazard reporting, and safety workflow orchestration.
• Develop robust validation frameworks, explainable AI methods, and safety-critical alignment techniques to ensure AI-driven operations tools provide accurate, trustworthy, and actionable decision support for human operators.
• Collaborate across multidisciplinary teams of computer scientists, AI researchers, and facility safety managers to integrate multi-agent operations tools into active laboratory safety management systems and risk mitigation protocols.
• Publish scientific findings in leading peer-reviewed AI/ML conferences and safety engineering journals, release open-source AI tools, contribute to research proposals, and uphold ORNL’s core values of Impact, Integrity, Teamwork, Safety, and Service.

• Ph.D. in Computer Science, Artificial Intelligence/Machine Learning, Electrical/Computer Engineering, Applied Mathematics, or a closely related discipline. Candidates who have completed all Ph.D. requirements and expect to receive their degree by the end of 2026 are also encouraged to apply.
• Strong research background in machine learning and deep learning (e.g., PyTorch, Tensor Flow),…