Postdoctoral Researcher - Model Engineering

Postdoctoral Researcher - Model Engineering

NLR is located at the foothills of the Rocky Mountains in Golden, Colorado, and is the nation's primary laboratory for energy systems research and development. Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.

At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.

Job Description

The National Laboratory of the Rockies (NLR), a leader in energy systems research, is seeking a highly motivated Postdoctoral Researcher to join our Grid Planning and Analysis Center (GPAC). This position will focus on tackling critical optimization challenges in medium-term power system planning like maintenance planning, hydro reservoir planning, and storage cycle budget allocations.

You will join a dynamic team of researchers developing cutting-edge computational tools to design and operate the next generation of reliable, resilient, and clean electric power grids. This role involves formulating and solving complex optimization problems and integrating them into the Sienna Platform for the simulation of large-scale systems.

The ideal candidate will have a strong foundation in operations research, control theory or power systems and a passion for applying these skills to real-world energy problems at large scale.

Primary Responsibilities

• Develop and implement novel mathematical optimization models (e.g., stochastic programming, robust optimization, mixed-integer linear programming) for medium-term grid planning.
• Design and code efficient algorithms for large-scale optimization problems using the Julia programming language and packages such as JuMP.jl. Experience with Xpress and Gurobi are a plus.
• Collaborate with a multidisciplinary team of engineers, computer scientists, and data scientists to put research insights into open-source software products.
• Publish research findings in leading academic journals and present at major international conferences.
• Contribute to the development of the open-source power systems modeling software Sienna and contribute to all the packages as needed.

Submission Guidelines

To apply, please submit your CV, a cover letter detailing your research interests and qualifications, a list of publications, and a link to your GitHub profile or other public code repository.

Basic Qualifications

Must be a recent PhD graduate within the last three years.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• A Ph.D. in Electrical Engineering, Operations Research, Industrial Engineering, Applied Mathematics, Control Systems, or a related field, awarded within the last three years.
• Demonstrated expertise in mathematical optimization techniques.
• Strong programming proficiency, with a willingness to code extensively in Julia.
• Applicants must provide a link to their GitHub profile or another public code repository for review.

Preferred Qualifications

• Domain knowledge in power system operations, economics, and planning problems.
• Experience with control theory concepts (e.g., Model Predictive Control, Dynamic Programming) and their application to energy systems applications
• Hands-on experience with JuMP.jl or similar algebraic modeling languages (e.g., Pyomo, GAMS, AMPL).
• Familiarity with high-performance computing (HPC) environments.
• Excellent communication skills and the ability to work effectively in a collaborative research environment.