Research & Development Engineer II

Overview

We are designing the grid of the future!

We are seeking an experienced R&D Engineer III to join our EPEResearch and Development team. This role combines expertise in power systems engineering with advanced computational research — including machine learning, adaptive control, and simulation-based modeling — to develop next-generation models that support grid planning, control, and reliability. The primary responsibility is to design, develop, and validate research-driven solutions and modeling frameworks that address emerging challenges in modern power systems, including data center interconnectionandlarge-scale system stability.

You will work closely with power system engineers, software developers, and research scientists to translate cutting‑edge research into practical, deployable models and tools.

How you can make an impact:

• Research & Model Development:
  
  Design, develop, and validate advanced modeling techniques — including machine learning-based surrogate models, digital twins, and stability certification methods — to support power systems planning and control applications.
• Automation & Programming:
  
  Work with Python and other relevant languages to automate research workflows, build adaptive control tools, advanced generator/load models, and streamline power system simulations and analysis.
• Technical Demonstration & Dissemination:
  
  Communicate research findings and technical model capabilities through internal presentations, technical reports, and peer-reviewed publications; support technical demonstrations for internal teams and clients as needed.
• Collaboration:
  
  Partner with power system engineers, software developers, and cross-functional research teams to integrate novel modeling approaches into EPE's engineering and software offerings.
• Client & Stakeholder Support:
  
  Serve as a technical resource for translating research capabilities into tailored solutions for client engagements and internal product development.
• Validation & Troubleshooting:
  
  Test, validate, and troubleshoot research software and models to ensure accuracy, reliability, and performance in real-world power system contexts.

Bring your passion, here's what’s needed:

• Ph.D. or Master's degree in Electrical Engineering with a focus on power systems, controls, or applied machine learning; a Ph.D. is strongly preferred given the research-intensive nature of this role.
• Demonstrated research experience (through publications, thesis work, or applied projects) in power systems stability analysis, control systems, or machine learning applications in energy systems.
• Deep understanding of power systems fundamentals, including transmission and distribution planning, grid dynamics, and stability analysis.
• Strong programming skills in Python, with experience using deep learning frameworks (e.g., PyTorch, Tensor Flow) and scientific computing libraries.
• Strong presentation and technical writing skills — capable of explaining complex research concepts to both technical and non-technical audiences.
• Familiarity with software development and testing practices to ensure robust, reliable research tools.
• Excellent problem-solving skills, particularly in diagnosing and resolving issues in simulation-based or data-driven power system models.

Preferred Qualifications:

• Proficiency in power system simulation software such as PSS/E, PSCAD, PSLF, Aspen, or TARA.
• Experience conducting power system studies such as Steady State, Short Circuit, or Dynamic and Transient Stability analysis.
• Experience with model predictive control (MPC), meta-learning, or in-context learning methods applied to dynamical or physical systems.
• Experience developing digital twins or surrogate models for grid-connected assets (e.g., data centers, BESS,…