Postdoctoral Research Associate - AI for Lab Operations

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

Benefits offered by this job

Medical benefits

Relocation assistance

Flexible work hours

Job summary

UT-Battelle is seeking a Postdoctoral Research Associate to lead research at the frontier of Generative AI, LLMs, and multi‑agent AI workflows for high‑consequence operations at ORNL. The role emphasizes practical tools for predictive safety, risk assessment, and incident prevention, with access to large‑scale GPU resources and opportunities to publish.

You will develop, fine‑tune, and evaluate AI architectures, collaborate across CSMD and operations teams, and contribute to trusted RAG systems

Qualifications

• Ph.D. in CS/AI/EE/Applied Math or related field; candidates may finish by end of 2026.
• Strong ML/DL background with practical experience in generative AI, multi‑agent AI systems, LLM fine‑tuning.
• Proficient Python and ML libraries (Hugging Face, LangChain, scikit‑learn, pandas).
• Publications or proven technical tool development in AI/ML/NLP.

Responsibilities

• Conduct original research and software tool development in Generative AI for operational safety and risk mitigation.
• Architect and deploy multi‑agent AI systems and RAG pipelines for automated risk scoring and hazard reporting.
• Develop validation frameworks, explainable AI methods, and safety‑critical alignment techniques.
• Collaborate with cross‑disciplinary teams to integrate AI tools into safety management systems.
• Publish in AI/ML and safety journals; contribute to proposals and open‑source releases.

Skills

Machine learning

Deep learning

Python

PyTorch

TensorFlow

Hugging Face

LangChain

LlamaIndex

Research

Education

PhD in Computer Science / AI / EE / Applied Math or related, expected by end of 2026

Tools

GPU clusters

Job description

Overview

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.

Requisition Id 17380

Overview

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.

Letters Of Recommendation

Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to [e-mail] with the position title and number referenced in the subject line.

Instructions To Upload Documents To Your Candidate Profile

• Login to your account via jobs.ornl.gov
• View Profile
• Under the My Documents section, select Add a Document

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
• 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.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email [e-mail].

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.