Center for Energy, Environmental, and Economic Systems Analysis (CEEESA) works on innovative research to enhance the resilience, efficiency, and sustainability of power grids. CEEESA is seeking talented and motivated researchers to provide support to enhance our capability in power system protection and reliability quantification areas.
The staff researcher will work with a team of researchers on developing novel protective solutions (models) to enhance the power system's reliability and resiliency. The candidate will perform theoretical study and algorithm development and support the principal investigator in DOE-sponsored projects. The candidate is expected to authorize peer-reviewed journal/conference publications, develop tools or software packages, 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.
Advanced degree in a relevant science or engineering field such as Electrical Engineering, Mechanical Engineering, Applied Mathematics, or other relevant domains.
The candidate is expected to have a basic understanding of protection systems in power grids.
Knowledge and independent research capability in linear systems, control, and communication systems.
Ability to design research projects in power system areas; develop, test, and apply relevant analytic methods; and clearly present results.
Skill in oral and written communication, particularly in effectively integrating information from various sources into cohesive analyses.
Skill in producing end-results within specific timeframes through a combination of self-motivated and manager-directed initiatives, often with tight deadlines.
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 protection system 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.
RD2: Bachelor's degree and 6+ years of work experience, or master's degree and 4+ years of work experience, or Doctorate and 2 years or their equivalents.
Research Development (RD)
Eng Systems Modeling-Simulation-Analysis 2
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