Center for Energy, Environmental, and Economic Systems Analysis (CEEESA) works on innovative research to enhance the resilience, efficiency, and sustainability of power grid. Advanced modeling and computation technologies are critical for building the future power grid with sufficient robustness and resiliency. CEEESA is seeking talented and motivated researchers to enhance its capability in solving energy challenges using innovative numerical methods.
The postdoc researcher will work with a team of researchers on developing advanced (dynamic and static) models for power system analyses. The postdoc researcher will perform theoretical study and algorithm development, especially in DOE-sponsored projects. The candidate is expected to authorize peer-reviewed journal/conference publications, develop open-source tools, and help disseminate research results to academic and industry communities. The successful candidate will draft research proposals and apply for funding from federal agencies and private industry.
A Ph.D. in Electrical Engineering, Mechanical Engineering, Applied Mathematics, or other relevant domains.
The candidate is expected to have a basic understanding of power system operations.
Knowledge and independent research capability in dynamic systems, control, and computational algorithms.
Proficient in implementing the algorithms and methods with mainstream programming languages such as Julia, Python, Java, C/C++, etc.
A successful candidate must have the ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
A successful candidate will have a solid background in power system dynamic modeling and transient analysis, a track record of publications in IEEE Transaction journals, and a highly skilled implementation capability.
Knowledge and independent research capability in power system dynamic model and simulation, especially inverter-based resource model, with track records of publications.
Proficiency in writing scientific research articles and presenting results at academic conferences.
Proficiency in implementing machine learning algorithms with mainstream frameworks, such as Tensorflow, Pytorch, Keras.
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.
Please note that all Argonne employees are required to be vaccinated against COVID-19. All successful applicants will be required to provide their COVID-19 vaccination verification as a condition of employment, subject to limited legally recognized exemptions to COVID-19 vaccination.
Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.