Argonne National Laboratory
Lemont, IL USA

Postdoctoral Appointee – Energy Systems

Onsite$72,879 – $121,465/yrGovernment Access Authorization (may be required)Posted Dec 7, 2025WebsiteLinkedIn

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About this role

Energy Systems and Infrastructure Assessment (ESIA) Division Overview

The Energy Systems and Infrastructure Assessment (ESIA) division provides the rationale for decision makers to improve energy efficiency. We develop and use analytic tools to help the U.S. achieve energy goals. ESIA also develops, deploys, and advances grid technologies that ensure a robust and secure U.S. grid transmission and distribution system. We collaborate with government agencies as well as companies to help move the nation toward an economy based on reliable energy.

Position Summary

The successful postdoctoral candidate will join a team of Argonne researchers and work closely with federal agencies and other national laboratories. The successful candidate will support technical and economic analyses of power systems with a particular focus on hydropower systems. The successful candidate will develop and apply methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and financial models. The position will include the analysis of hydropower operation and expansion, optimization and equilibrium, market penetration, and interdependencies. This description documents the general nature of work but is not intended to be a comprehensive list of all activities, duties and responsibilities required.

Key Responsibilities

  • Develop and implement power system modeling tools, with emphasis on simulation and optimization of hydropower systems and their integration with broader electricity markets.
  • Conduct research on electricity system operations, planning, and market design, including evaluation of economic and environmental trade-offs.
  • Contribute to projects involving capacity expansion, production cost modeling, and equilibrium modeling of power systems.
  • Design and apply mathematical optimization models, including linear, mixed-integer, and stochastic programming.
  • Work with programming languages such as Python, Julia, or C++ to build robust analytical tools and perform large-scale data analysis.
  • Collaborate with internal teams and external stakeholders, including U.S. Department of Energy offices and other national laboratories.
  • Communicate research findings through peer-reviewed publications, technical reports, and presentations at scientific conferences.
  • Support proposal development and stay abreast of developments in the field through literature reviews and professional engagement.

Position Requirements

  • Recent or soon-to-be completed (typically within the last 0-5 years) Ph.D. in engineering, operations research, computer science, applied mathematics, or a related field.
  • Demonstrated expertise in mathematical optimization techniques and solvers (e.g., Gurobi, CPLEX), including linear, mixed-integer, or stochastic programming.
  • Proficiency in at least one modern scientific programming language (Python, Julia, or C++ preferred).
  • Knowledge of power system operations, electricity market mechanisms, and energy system modeling.
  • Analytical and problem-solving skills, with the ability to work independently and collaboratively in a team environment.
  • Proven research record, evidenced by peer-reviewed publications and conference presentations.
  • Skilled written and verbal communication skills at all levels of the organization.
  • Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
  • This position requires an on-site presence at the Argonne campus in Lemont, Illinois.

Preferred Qualifications

  • Experience with hydropower modeling, energy storage systems, or renewable integration.
  • Familiarity with production cost models or capacity expansion models.
  • Experience collaborating with government agencies or working in multi-institutional research environments.
  • Understanding of financial and economic evaluation of energy technologies.