Postdoctoral Appointee: (Power System Modeling and Transient Study)
- Argonne National Laboratory
- Location: Lemont, IL
- Job Number: 7107071 (Ref #: 413876)
- Posting Date: Aug 3, 2022
- Application Deadline: Open Until Filled
Job Description
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.
Position Requirements
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.
Preferred Qualifications:
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 Family
Postdoctoral FamilyJob Profile
Postdoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
Full timeAs 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.
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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.
