Postdoctoral Researcher: Power Systems Modeling and Analysis

National Laboratory of the Rockies • Golden, CO

4d • Onsite

About The Position

The Price Signals for Grid Services Group within the Grid Planning and Analysis Center (GPAC) at the National Laboratory of the Rockies (NLR) is hiring a postdoctoral researcher to join a highly interdisciplinary and collaborative team of researchers developing and applying state-of-the art power system models to conduct leading-edge analyses. GPAC research staff contribute to an exciting portfolio of energy research and analysis, applying advanced modeling and simulation tools to optimally plan for, design, and analyze distribution and bulk power systems to ensure reliability, affordability, and security. We are researchers, engineers, software developers, modelers, physicists, product managers, thought leaders, system thinkers, and life-long learners. Our staff engage in different research projects and find ways to contribute uniquely based on our interests and skillsets. Example types of ongoing research and analysis include: Innovating new data, models, tools, and systems that are needed for the future grid Working directly with U.S. communities to support grid reliability, affordability, and security Examining the necessary grid services and market structures to support a reliable and affordable future grid Developing the design and integration of new technologies, loads, and systems NLR is the nation's primary national laboratory for critical minerals, energy innovation, and energy security. We seek to bridge research with real-world applications to advance new energy materials and technologies that lower costs, boost the economy, strengthen security, and deliver abundant and reliable energy. We partner with DOE, other federal agencies, states, utilities, ISO/RTOs, communities, and technology developers on grid planning and analysis. Our work informs decision makers and utilities by developing and analyzing future grid scenarios that answer big questions about how the electric power system is transforming. Come join a team whose mission is to ensure a reliable, affordable, and secure energy system for the United States!

Requirements

• Must be a recent PhD graduate within the last three years.
• Must meet educational requirements prior to employment start date.
• Proficiency using Python
• Knowledge of U.S. energy systems
• Proficiency in applied statistical methods and quantitative methods
• Previous experience with energy and electricity modeling and data
• Must be able to work independently and as part of a team.

Nice To Haves

• Demonstrated experience presenting research findings to broad—technical and non-technical—audiences
• Exceptional writing skills and a demonstrated record of publication in the technical/peer-reviewed literature.

Responsibilities

• Contributing to the development and implementation of new advanced methods for capacity expansion modeling
• Researching rules, trends, and issues in power system planning and operation—e.g., transmission planning, changes in electricity demand, large load growth—and consider how to implement them into electric sector models
• Executing quality control methods
• Researching, acquisition, organization, and analysis of large data sets
• Developing new data architectures to generically and flexibly describe infrastructure systems
• Collaborating with analysts on other modeling teams to relate inputs and outputs across models
• Executing scenarios, and analyzing and interpreting results for reporting
• Writing and publishing results of analyses in peer-reviewed journals and technical reports
• Assisting in the development of proposals for new work

Benefits

• medical, dental, and vision insurance
• short-term disability insurance
• pension benefits
• 403(b) Employee Savings Plan with employer match
• life and accidental death and dismemberment (AD&D) insurance
• personal time off (PTO) and sick leave
• paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree