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 interconnection and large-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.

• 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.

• 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,…