Postdoctoral AI Researcher in Power Systems

Brookhaven National Laboratory • Upton, NY

5d • Onsite

About The Position

The Energy and Photon Science Directorate advances basic science that underpins discoveries and breakthroughs for energy systems. The appointment will be for a one-year with an opportunity for a one-year renewal to perform research in the area of electric power grids based on funding and individual performance. The successful candidate will contribute to the development of next-generation AI foundation models and AI-enabled workflows for electric applications. In particular, the position focuses on advancing GridFM, a grid foundation model for power systems. The role offers unique opportunities to contribute to cutting-edge research while helping translate AI innovations into real-world utility applications that support grid modernization, resilience, and large-scale electrification.

Requirements

• Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field.
• Strong background in machine learning and deep learning.
• Experience with PyTorch, JAX, TensorFlow, or similar frameworks.
• Some experience developing Graph Neural Networks (GNNs), Graph Transformers, or foundation-model architectures.
• Familiarity with model training, fine-tuning, evaluation, and deployment.
• Understanding of uncertainty quantification, model robustness, and physics-informed AI.
• Experience with GPU computing and large-scale model training.
• Demonstrated ability to conduct independent research.
• Candidates must have completed all degree requirements by the commencement of employment.
• Postdoctoral and/or R&D position experience not exceeding a combined total of 5 years after obtaining a PhD (excluding time associated with family planning, military service, illness or other life-changing events).

Nice To Haves

• Familiarity with distributed computing, HPC environments, and cloud platforms.
• Experience building production-quality software and ML pipelines.
• Familiarity with Git, CI/CD, containerization (Docker), and reproducible workflows.
• Experience developing APIs and workflow orchestration systems.
• Experience optimizing AI workloads for performance and scalability.
• Basic knowledge of electric power systems, transmission/distribution networks, power flow, optimal power flow, contingency analysis, or grid planning.
• Familiarity with tools such as PowerModels, MATPOWER, PSS/E, GridLAB-D, OpenDSS, or similar.
• Experience with mathematical optimization, mixed-integer programming, stochastic optimization, or decision analytics.
• Familiarity with Gurobi, CPLEX, Pyomo, JuMP, or related tools.
• Experience with LLM-based workflows, tool-calling agents, MCP architectures, retrieval systems, or AI copilots.
• Familiarity with multi-agent systems and decision-support applications.

Responsibilities

• Extend current GridFM capabilities for distribution networks
• Develop scalable graph-based machine learning or related models
• Expand training data generation capabilities
• Create benchmarks and test developed models

Benefits

• Comprehensive employee benefits program

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree