Postdoctoral Research Associate - AI for Lab Operations

Oak Ridge National Laboratory; Oak Ridge (TN); On-site; USD 65,000 - 90,000; Full time

Job summary

Oak Ridge National Laboratory (ORNL) seeks a Postdoctoral Research Associate to advance Generative AI, LLMs, and human-in-the-loop agentic AI for real-world lab operations. You will build multi-agent AI tools for hazard identification, risk mitigation, and safety workflows, collaborating with ML researchers and domain safety experts.

Ideal candidates have a PhD in a related field, strong ML/DL expertise, and a track record in AI tool development or publications.

Qualifications

• PhD in Computer Science, AI/ML, EE, or related field; degree by end of 2026 encouraged.
• Strong ML/DL background with practical generative AI and multi-agent systems experience.
• Proficient Python and ML libraries such as PyTorch, TensorFlow, Hugging Face.
• Publish record or notable tool development in AI/ML/NLP domains.

Responsibilities

• Conduct original research in Generative AI for safety and operations.
• Architect and deploy multi-agent AI systems and RAG pipelines.
• Develop validation, explainable AI, and safety-aligned methods.
• Collaborate with researchers and safety experts to integrate tools into lab systems.
• Publish findings and contribute to open-source AI tools.

Skills

Generative AI

Multi-agent AI

Python

PyTorch

TensorFlow

Hugging Face

LangChain

LlamaIndex

Scikit-learn

Pandas

Education

PhD in CS/AI/EE/Applied Math

Tools

Hugging Face

LangChain

LlamaIndex

scikit-learn

Pandas

Job description

Postdoctoral Research Associate - AI for 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 at scale. The 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.

Major Duties/Responsibilities:

• 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.

Basic Qualifications:

• 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, TensorFlow), with practical experience in generative AI, multi-agent AI systems, LLM fine-tuning, and building AI tools for operational or text-heavy domain applications.
• Strong Python software engineering skills and proficiency with common ML libraries and frameworks (e.g., Hugging Face, LangChain/LlamaIndex, scikit-learn, pandas).
• Demonstrated research record evidenced by peer-reviewed publications in top AI/ML/NLP venues or technical tool development in complex domains, with strong oral and written communication skills.

Preferred Qualifications:

• Experience designing multi-agent AI orchestrations, agentic tool-use frameworks, vector databases, and enterprise-grade RAG systems for automated risk assessment or operational workflows.
• Direct experience in functional safety modeling, hazard identification, risk mitigation strategies, or reinforcement learning with human feedback (RLHF) for safety-critical domain applications.
• Experience building scalable AI operations software tools and deploying containerized ML pipelines on GPU clusters.
• Record of open-source contributions to AI/ML tools, experience working directly with domain operations teams, or collaborative R&D across national laboratories, industry, or academia.
• Experience using LaTeX for writing scientific manuscripts.

Special Requirements:

• Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.
• This position requires the ability to obtain and maintain an HSPD-12 PIV badge.

For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.

To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

For foreign national candidates:

If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.

About ORNL:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.