Postdoctoral Researcher: Bulk Grid Monitoring and Dynamic Security Assessment

Postdoctoral Researcher: Bulk Grid Monitoring and Dynamic Security Assessment Location: Golden, Colorado Position Type: Postdoc (Fixed Term) Hours per Week: 40 Job Summary The Grid Automation and Control (GAC) Group of the Power Systems and Engineering Center (PSEC) at the National Laboratory of the Rockies (NLR) is looking for an exceptional Ph.D. graduate to support research in the operation, modeling, and simulation of the power grid, while the power grid is transitioning to a modern grid with increasing growth of load and inverter-based resources. Responsibilities Develop measurement‑based modeling techniques for power systems, including the use of PMU and other high‑resolution measurements to identify dynamic parameters for black‑box models. Conduct measurement‑based dynamic stability assessments, such as fault detection, real‑time inertia estimation, oscillation detection and analysis, and system strength evaluation, etc. Develop software tools and algorithms for measurement‑based stability monitoring and analysis tool, as well as dynamic model calibration tools that can be deployed in future control room environments. Contribute to the development of measurement‑informed digital twins for power system analysis and operational decision support. Maintain and enhance existing NLR platforms and tools used for testing innovative research ideas. Prepare and present results in the form of technical reports and presentations. Write and publish research findings in peer‑reviewed journals, transactions, conference proceedings, and technical reports. Basic Qualifications Must be a recent Ph.D. graduate within the last three years. Must meet educational requirements prior to employment start date. Relevant Ph.D. or Ph.D. candidate in Electrical Engineering or Computer Science or related fields. Experience working with PMU data or other grid measurement data. Advanced modeling expertise in various power systems modeling. Experience with computer programming or software development, and Python is preferred. Strong analytical and communication skills. Preferred Qualifications Strong background in power system modeling, simulation and dynamic analysis. Knowledge of system identification, signal processing, or dynamic parameter estimation techniques. Experience working with wide‑area measurement systems (WAMS), PMU data, or other high‑resolution grid measurement data. Experience in one or more of the following areas: oscillation detection and analysis, inertia estimation, dynamic model validation, or real‑time monitoring. Experience handling large‑scale operational datasets such as SCADA, WAMS, or PMU measurements is desirable. Familiarity with machine learning, data analytics, or data‑driven modeling approaches applied to power systems is a plus. Software development experience is a plus, including programming in Python, GAMS, C++, or other languages. Excellent written and verbal communication skills. Benefits Medical, dental, and vision insurance; short‑term disability insurance; pension benefits; 403(b) Employee Savings Plan with employer match; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; paid holidays. Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. #J-18808-Ljbffr National Renewable Energy Laboratory