Graduate Research Associate, Post Masters- Power Systems
About The Position
The SRNL Doctoral Research Fellow in Power Systems will contribute to SRNL’s mission of advancing the resilience and intelligence of the nation’s energy infrastructure by conducting multidisciplinary research at the intersection of power systems, physics-informed digital twins, and AI/ML. The Fellow will join a strategic workforce-development pipeline designed to address the critical national shortage of U.S. PhD scientists with expertise in dynamic and transient analysis of advanced energy systems. The Fellow will work alongside SRNL scientists and university faculty on energy-systems research topics encompassing dynamic and transient analysis of electrical, thermal, and mechanical energy systems; real-time simulation using Controller Hardware-in-the-Loop (CHIL) and Power Hardware-in-the-Loop (PHIL); and the development of physics-informed AI/ML methods and digital-twin capabilities for nuclear-SMR, grid, and renewables applications. Fellows are provided an immersive learning environment to develop into the next generation of multidisciplinary energy researchers, integrate academic coursework with hands-on national-laboratory R&D, and make impactful contributions to ongoing DOE programs. Work scope may include contributions to the design and operation of CHIL/PHIL testbeds; development and validation of physics-informed machine-learning models; AI-driven digital-twin construction for cyber-physical energy systems; data-driven analysis of phasor measurement, EMS, and operational utility data; and participation in publications and conference presentations in collaboration with SRNL principal investigators and university advisors.
Requirements
- Post Masters degree in Power Systems or related field
- Expertise in dynamic and transient analysis of advanced energy systems
- Experience with Controller Hardware-in-the-Loop (CHIL) and Power Hardware-in-the-Loop (PHIL)
- Knowledge of physics-informed AI/ML methods and digital-twin capabilities
- Familiarity with nuclear-SMR, grid, and renewables applications
Responsibilities
- Contributions to the design and operation of CHIL/PHIL testbeds
- Development and validation of physics-informed machine-learning models
- AI-driven digital-twin construction for cyber-physical energy systems
- Data-driven analysis of phasor measurement, EMS, and operational utility data
- Participation in publications and conference presentations in collaboration with SRNL principal investigators and university advisors
Benefits
- Highly competitive Medical, Dental, and Vision options including HSA options with company provided seed
- Short- & Long-Term Disability (company paid)
- Life Insurance Non-Contributary 1X salary (company paid)
- AD&D Non-contributary 1x salary (company paid)
- Savings & Investment plan: Qualified Non-Elective Company Contribution of 5% each pay period with immediate vesting
- Company match 50 cents/dollar up to 8% (5 yrs. vesting in company match)
- Contributory Life Insurance up to 5x Salary with $1M Cap
- Contributory AD&D (employee, spouse and children)
- Paid Time Off
- Employee Assistance Plan
- Competitive relocation package
- Domestic and international relocation assistance is available for certain positions
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
