
Graduate Intern - Synchrophasor Research - Engineering Analytics & Modeling
- Glen Allen, VA
- Training
- Full-time
- Support the development of an array of analytical tools and capabilities aimed at observing, diagnosing, and surfacing system behavior that can help improve grid management.
- Explore new research areas for time-series analysis in power systems.
- Develop and evaluate new system evaluation methodologies built on the premise of improving our observability of dynamic system behaviors through the creative use of signal analysis.
- Engineering principles: A strong engineering background, preferably in electric power systems. Other engineering backgrounds may be considered if presented in combination with a strong electric power background.
- Power system fundamentals: steady-state and dynamic stability analysis (e.g. PV curve, transient stability, eigen analysis). The candidate should be able to extend this theoretical knowledge to large-scale, practical problems to identify implementable solutions.
- Data Science & Data Analysis: The candidate should possess strong software development skills and frequently use code to solve analytical and automation problems. More specifically, the candidate must demonstrate a high degree of proficiency in developing tools and performing analysis using Python and the common Python scientific computing libraries.
- Real-world measurement data analysis: experience analyzing and modeling of electric power systems (e.g. inertia estimation, mode estimation, model validation, state estimation).
- Operational model analysis: This includes the application of signal processing techniques to power system analysis (Fourier transform, SVD, time-frequency analysis).
- Autonomy and self-starting: We are spearheading a brand-new industry capability; we are seeking candidates with the ability to operate independently while aligning to the joint mission of our team.
- Critical thinking: Our team requires an ability to think abstractly, pursue unknown unknowns, and the motivation to persevere even in failure. What we are solving for is new and challenging - we require out of the box thinkers.
- Candidates must have completed a Bachelor's degree in an engineering discipline and be working on a Master's or preferably a Ph.D. degree from an ABET accredited Engineering program at a four year or post-graduate college or university.
- Must have an anticipated graduation date of Winter 2026 or later.
- Candidates must have a 3.2 minimum cumulative GPA.
- Electrical Engineering with a focus on power systems is strongly preferred.
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·Headquarters: Richmond, VA
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