Postdoctoral AI Researcher in Power Systems
Listed on 2026-08-22
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Overview
The Energy and Photon Science Directorate advances basic science that underpins discoveries and breakthroughs for energy systems. The appointment is for a one-year term with an option for a one-year renewal, funded by project and performance. The successful candidate will contribute to the development of next‑generation AI foundation models and AI‑enabled workflows for electric applications, focusing on advancing GridFM, a grid foundation model for power systems.
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
- 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, Tensor Flow, 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.
- 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 Power Models, 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.
Candidates must have completed all degree requirements by the commencement of employment. BNL policy requires that after obtaining a Ph.D., eligible research associate appointments may not exceed a combined total of five years of relevant post‑doc and/or R&D experience, excluding time associated with family planning, military service, illness, or other life‑changing events.
The selected candidate must be able to obtain and maintain a DOE UPIV credential, as required by DOE Order 206.2 Chg. 2.
The base salary for this position ranges from $70,200 to $85,000 per year, commensurate with experience and peer group.
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