Postdoctoral Research Associate - AI Models for Power Grid System

Oak Ridge National Laboratory; Oak Ridge (TN); On-site; USD 70,000 - 105,000; Full time

Benefits offered by this job

Medical benefits

Retirement plans

Flexible work hours

On-site amenities

Job summary

Oak Ridge National Laboratory (ORNL) invites applications for a Postdoctoral Research Associate to advance AI and DL for power grid systems. You will design scalable models, build HPC-ready workflows, and contribute to scalable data management on leadership-class systems.

The role requires a PhD in CS or AI-related field, experience with PyTorch, SLURM/PBS, and strong publication credentials. Collaborative, fast‑paced, research environment with DOE resources and open avenues for extensions.

Qualifications

• PhD in CS or AI field completed within the last 5 years.
• Demonstrated expertise in scalable deep learning and distributed training (PyTorch).
• Experience with HPC systems and multi-node workflows (CPU/GPU).
• Expertise in scalable data management for AI/ML workloads.
• Proficient in SLURM/PBS scriptwriting for HPC clusters.
• Strong Linux, bash, Git, Python skills; reproducible environments.
• Proven ability to write advanced software and DL algorithms in Python.
• Experience with OO programming and modern software engineering practices.
• Strong written/oral communication with publications record.

Responsibilities

• Design and deploy scalable AI/DL models for power grid systems.
• Develop HPC-ready workflows for distributed training and large-scale inference.
• Create robust Linux bash and job submission scripts for SLURM/PBS.
• Publish results in journals/conferences and present at workshops.
• Collaborate with multidisciplinary teams to advance AI/DL research.

Skills

PhD in CS/AI

Scalable DL (distributed)

HPC / multi-node

Data management for AI/ML

SLURM & PBS scripting

Linux / Bash / Git

Python & DL algorithms

Software engineering practices

Technical writing & talks

Education

PhD in Computer Science or AI-related field

Tools

PyTorch

SLURM

PBS

Python

Git

Job description

Overview

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.

Requisition Id 16687

Overview

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.

The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected to bring strong expertise in scalable deep learning, high-performance computing (HPC), scalable data management, Linux environments, and production-quality scripting for HPC workflows.

Major Duties/Responsibilities

• Participate in the design, implementation, and deployment of scalable AI/DL models for power grid systems, including surrogate models and foundation-model workflows for OPF and related grid simulation tasks.
• Develop and maintain HPC-ready software workflows for distributed training, large-scale inference, scalable data ingestion, and data management on leadership-class computing systems and institutional clusters.
• Write robust Linux bash scripts and job submission scripts for SLURM and PBS environments, including multi-node GPU/CPU workflows, monitoring, restart, and post-processing pipelines.
• Author peer reviewed papers for journals and conferences, technical reports, open-source software, and represent the organization by making technical presentations at workshops and conferences.
• Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, electrical engineers, domain scientists, and applied mathematicians conducting basic and applied AI/DL research in support of the Laboratory’s missions.

Basic Qualifications:

• A PhD in computer science or an AI-related field completed within the last 5 years.
• Demonstrated expertise in scalable deep learning, including distributed training and/or large-scale inference using modern AI frameworks such as PyTorch.
• Demonstrated experience with high-performance computing systems, including multi-node workflows on CPU and/or GPU clusters.
• Demonstrated expertise in scalable data management for AI/ML workflows, including efficient data preprocessing, storage, streaming, and I/O for large scientific datasets.
• Demonstrated experience writing SLURM and PBS job submission scripts for HPC clusters, including batch workflows, job arrays, environment setup, and restart logic.
• Demonstrated expertise with the Linux operating system, bash scripting, Git, Python, and reproducible software environments.
• Demonstrated expertise in writing advanced software in Python and in the design and implementation of deep learning algorithms.
• Expertise in object-oriented programming, scripting languages, and modern software engineering practices for research codes.
• Demonstrated effective written and oral communication skills, a proven publication record, and effective interpersonal skills.

Preferred Qualifications:

• Knowledge of graph neural networks and other geometric deep learning approaches for graph-structured scientific or engineering data.
• Background in electrical engineering, power systems, grid modeling, or power system optimization.
• Experience with optimal power flow and grid simulation solvers or toolchains, such as MATPOWER, PSS/E, PowerModels, or related open-source or commercial packages.
• Experience working in a multi-disciplinary research environment that follows modern software quality standards, including version control, unit testing, documentation, and continuous integration.
• Motivated self-starter with the ability to work independently, participate creatively in collaborative teams, function well in a fast-paced research environment, and adapt to evolving project needs.

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 for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

Candidates are asked to submit a detailed cover letter describing their experience relative to the duties and qualifications described in this posting with their application.

Please submit three letters of reference when applying to this position. You can 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

Technical questions:

Massimiliano Lupo Pasini ( [e-mail] ), Alex Plotkowski ( [e-mail] )

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.

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.