Postdoctoral Researcher: Power System Operation and Optimization

National Renewable Energy Laboratory; Golden (CO); On-site; USD 76,600 - 126,400; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Pension plan

403(b) savings plan with employer match

Paid time off and holidays

Job summary

The National Renewable Energy Laboratory is seeking a Postdoctoral Researcher in Power System Operation & Optimization. This position requires in-person work in Golden, Colorado, with responsibilities including developing power system modeling techniques and publishing research.

The ideal candidate will possess a Ph.D. in a relevant field and have experience with tools such as OpenDSS and CPLEX. The role offers a competitive salary and a comprehensive benefits package.

Qualifications

• Ph.D. or Ph.D. candidate in a relevant field completed within the last three years.
• Experience in power system modeling, optimization, and control.
• Proficiency with at least one power-system software tool.

Responsibilities

• Develop and apply power system modeling and optimization techniques.
• Design control strategies for various energy management systems.
• Publish research results in peer-reviewed journals.

Skills

Power system modeling

Optimization techniques

Control strategies

MATLAB programming

Python programming

Education

Ph.D. in Electrical Engineering, Computer Science, or related field

Tools

OpenDSS

PSCAD

PSS/E

CPLEX

CVXPY

Pyomo

GAMS

Job description

Postdoctoral Researcher – Power System Operation & Optimization

Location: Golden, Colorado (South Table Mountain Campus, NLR). Position type: Fixed‑term Postdoc (40 hours/week). In‑person work required.

Overview

The Grid Automation and Controls Group of the Power Systems and Engineering Center (PSEC) at the National Laboratory of the Rockies (NLR) is looking for a Ph.D. graduate to support research in power grid operation and optimization.

Core Responsibilities

• Develop and apply power system modeling, operation, and optimization techniques.
• Design energy‑management and data‑driven control strategies for ADMS, DERMS, microgrids, and home energy management.
• Create optimization schemes or data‑driven controls to enhance grid reliability, resilience, and automation.
• Conduct research and collaborate with internal and external partners.
• Publish research results in peer‑reviewed journals.

Basic Qualifications

• Ph.D. or Ph.D. candidate in Electrical Engineering, Computer Science, or related field completed within the last three years.
• Experience in power system modeling, optimization, and control.
• Proficiency with at least one power‑system software tool (OpenDSS, PSCAD, PSS/E).
• Experience with at least one optimization solver/platform (CPLEX, CVXPY, Pyomo, GAMS).
• Proficiency in MATLAB or Python programming.

Preferred Qualifications

• Knowledge of microgrids, grid resilience, and grid cybersecurity.
• Experience with market participation, demand response, or virtual power plant concepts.
• Experience with transmission and distribution coordination.
• Proficiency in commercial or open‑source optimization solvers (GAMS, Gurobi, CPLEX).
• Software development experience in Python, C++, or other languages.
• Excellent writing and verbal communication skills.
• Strong record of scientific publications.

Salary & Benefits

Annual Salary Range (full‑time, 40 hrs/week): $76,600 – $126,400.

Benefits include medical, dental, and vision insurance; short‑term disability insurance; pension plan; 403(b) savings plan with employer match; life and accidental death & dismemberment insurance; paid time off, sick leave, and paid holidays.

Equal Opportunity

All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity, genetic information, marital status, domestic partnership status, veteran status, national origin, religion, creed, sex, sexual orientation, or any other status protected by federal, state, or local laws.

Reasonable accommodations will be provided to qualified individuals as requested.