Postdoctoral Research Associate - AI Models Power Grid System

Postdoctoral Research Associate - AI Models for Power Grid System

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 tool chains, such as MATPOWER, PSS/E, Power Models, 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 postdoc recruitment with the position title and number referenced in the subject line.

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…