AI/ML for Power System Analysis, Power Flow, and State Estimation Fall Student Engineer
Position Title: AI/ML for Power System Analysis, Power Flow, and State Estimation Fall Student Engineer
Requisition ID: REQ-4018
Position Type: Full time
About Us:
About Us
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EPRI provides thought leadership, industry expertise, and collaborative value to help the electricity sector identify issues, technology gaps, and broader needs that can be addressed through effective research and development programs for the benefit of society.
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Job Title:
AI/ML for Power System Analysis, Power Flow, and State Estimation Fall Student EngineerLocation:
Knoxville, TNJob Summary and Description:
This is an internship position for a student to support R&D projects related to AI-driven power system modeling, including power flow, state estimation, and large-scale grid analytics under high renewable penetration. Looking for students who can work at minimum in the 2026 Fall semester (August-December).
Duties & Responsibilities:
The student must be familiar with the following:
Basic familiarity with integrating physical constraints (power flow equations, network limits) into data-driven models (physics-informed ML concepts)
Understanding of representing power systems as graphs and applying graph-based learning methods (e.g., graph neural networks)
Exposure to developing machine learning models (preferably deep learning) for power system applications
Working knowledge of AC/DC power flow, state estimation, and grid modeling fundamentals
Procedure of running power flow simulations using tools such as PSS®E, PSLF, Pandapower, or MATPOWER, and understanding system modeling workflows
Procedure of generating datasets using simulation tools for varying load, generation, and contingency conditions (N-1, N-k)
Qualifications:
Minimum 1 year of Master’s or PhD (in Electrical Engineering focusing on Power systems)
Ideal Candidate:
Electrical engineering PhD student with emphasis on AI for power systems
Strong understanding of power flow and/or state estimation methods
Familiarity with power system simulation tools (preferably PSS®E, PSLF, Pandapower, or MATPOWER)
Strong programming skills (preferably in Python, MATLAB is a plus)
Experience with machine learning or deep learning frameworks (e.g., PyTorch or TensorFlow)
Exposure to graph neural networks will be considered a plus
Experience with data processing, numerical computing, and model development
Strong technical writing and presentation skills
The hourly rate range for Student positions are:
Undergraduate: $16-29 per hour
Masters: $27-33 per hour
Ph.D: $31-36 per hour
These ranges are an estimate, and the actual hourly rate may vary based on various factors, including without limitation applicant's education, experience, skills, and abilities, as well as internal equity and alignment with market data. The hourly rate may also be adjusted based on applicant's geographic location.
As an EPRI Student, you will not participate in EPRI’s Benefit Programs which includes health insurance, retirement benefits, vacation, sick leave (except as set required by law) and holiday pay. However, as a Student employee you are eligible for the benefits of Social Security, State Disability Insurance, and Workers’ Compensation Insurance.
For Student positions which require one to relocate to an EPRI office. Relocation assistance is not provided and the student will be responsible for covering all relocation costs/expenses.
EPRI participates in E-Verify, an online system operated jointly by the Department of Homeland Security and the Social Security Administration (SSA). EPRI uses the system to check the work status of new hires by comparing information from the employee's I-9 form against SSA and Department of Homeland Security databases.
EPRI is an equal opportunity employer. EEO/AA/M/F/VETS/Disabled
Together . . . Shaping the Future of Energy.
www.epri.com
Equal employment opportunity, including veterans and individuals with disabilities.
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