Postdoctoral AI Researcher in Power Systems

Brookhaven National Laboratory; New York (NY); On-site; USD 70,200 - 85,000; Full time

Job summary

Brookhaven National Laboratory invites applications for a Postdoctoral AI Researcher in Power Systems, based in Upton, NY. The role focuses on AI-enabled workflows for electric power grids and the GridFM foundation model, with emphasis on distribution networks and large-scale electrification.

The successful candidate will extend GridFM capabilities, develop graph-based ML models, generate data, and benchmark them.

Qualifications

• PhD 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) 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.

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.

Skills

Machine learning

Deep learning

PyTorch/JAX/TF

Graph neural networks

Uncertainty quantification

GPU computing

Independent research

Education

PhD in CS/EE/Math/Physics

Tools

PowerModels

MATPOWER

PSS/E

GridLAB-D

OpenDSS

Docker

Git

Job description

## Postdoctoral AI Researcher in Power SystemsApplylocations: Upton, NYtime type: Full timeposted on: Posted 3 Days Agojob requisition id: JR102531The 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.**Essential Duties and 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**Required Knowledge, Skills, and Abilities:*** 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.**Preferred Knowledge, Skills, and Abilities:*** 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.**Other Information:*** Candidates must have completed all degree requirements by the commencement of employment.* BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in and R&D position, excluding time associated with family planning, military service, illness or other life-changing events.* Brookhaven Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $70,200 - $85,000/ year. You will be placed at the level and salary commensurate with your experience. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group. **Brookhaven National Laboratory is committed to employee success and we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Review more information at** **BNL | Benefits Program** Brookhaven National Laboratory requires all non-badged personnel including visitors to produce a REAL-ID or REAL-ID compliant documentation to access Brookhaven National Laboratory – view more information at www.bnl.gov/real-id. This is due to nationwide identification requirements for federal site access as required by the federal REAL ID Act. **Those not in possession of a REAL ID-compliant document will not be permitted to access the site which includes access to the Laboratory for interviews**. As a U.S. Department of Energy laboratory, Brookhaven National Laboratory requires employees to obtain and maintain a DOE Uncleared Personal Identity Verification (UPIV) credential in accordance with Homeland Security Presidential Directive 12 (HSPD-12) requirements. The credentialing process is completed as part of onboarding and enables access to DOE facilities and information systems. As a condition of employment, the selected candidate must be able to obtain and maintain a UPIV credential. These requirements are established under DOE Order 206.2 Chg. 2, *Identity, Credential, and Access Management (ICAM-* Identity, Credential, and Access Management (ICAM)*)*, and DOE Order 473.1A- Physical Protection Program- Physical Protection Program.