Postdoctoral AI Researcher in Power Systems

Posted 7 Hours Ago
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Upton, NY, USA
In-Office
70K-85K Annually
Junior
Artificial Intelligence • Energy • Defense
The Role
Perform postdoctoral research to advance GridFM foundation models for electric power grids: extend capabilities to distribution networks, develop scalable graph-based ML models, expand training-data generation, create benchmarks, and evaluate, fine-tune, and deploy models with attention to uncertainty quantification, robustness, and large-scale GPU training.
Summary Generated by Built In

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.

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.


About Us

Brookhaven National Laboratory (www.bnl.gov) delivers discovery science and transformative technology to power and secure the nation’s future. Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research. The Lab is primarily supported by the U.S. Department of Energy’s (DOE) Office of Science. Brookhaven Science Associates (BSA) operates and manages the Laboratory for DOE. BSA is a partnership between Battelle and The Research Foundation for the State University of New York on behalf of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities for Veterans at Brookhaven National Laboratory.


Equal Opportunity/Affirmative Action Employer


Guided by our core values of integrity, responsibility, innovation, respect, and teamwork, Brookhaven Science Associates is an Equal Employment Opportunity Employer-Vets/Disabled. We are committed to fostering a respectful and collaborative environment that fuels scientific discovery. We consider all qualified applicants without regard to any characteristic protected by law. All qualified individuals are encouraged to apply. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.  *VEVRAA Federal Contractor


BSA employees are subject to restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation at the time of hire for review by Brookhaven. The full text of the Order may be found at: https://www.directives.doe.gov/directives-documents/400-series/0486.1-BOrder-a/@@images/file

Skills Required

  • Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or related field.
  • Strong background in machine learning and deep learning.
  • Experience with PyTorch, JAX, TensorFlow, or similar frameworks.
  • Experience developing Graph Neural Networks, 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.
  • 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.
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The Company

What We Do

Brookhaven National Laboratory (BNL) is a U.S. Department of Energy national laboratory conducting fundamental and applied research in nuclear and particle physics, photon sciences, energy security, quantum and information science, and artificial intelligence. BNL operates large user facilities and partners with academia and industry to translate scientific discoveries into technologies and programs supporting energy, national security, and public-benefit applications.

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