The Energy Systems and Infrastructure Assessment (ESIA) division at Argonne provides the rationale for decision makers to improve energy efficiency. ESIA develops and uses analytic tools to help the U.S. achieve energy goals. ESIA develops, deploy, and advances grid technologies that ensures a robust and secure U.S. grid transmission and distribution system. ESIA also collaborates with government agencies as well as companies to help move the nation toward an economy based on reliable energy.
The successful postdoctoral candidate will join a team of Argonne researchers and work closely with federal agencies and other national laboratories. The candidate will develop power systems and electricity market modeling, and analytics tools that support energy, economic, and financial analyses of power grid planning and operations, and the interaction with other infrastructures. Some of these tools will require the development of underlying optimization methodologies and analytics frameworks. The successful candidate will conduct research related to a wide range of topic areas including the analysis of energy and power systems, optimization of veriable energy resources, electricity market design and operation, integration of other emerging technologies, and interdependencies between power grid, transportation, and water systems. This position may require domestic and international travel.
Provides support to develop and implement power grid planning/operations algorithms and tools and conducts data analysis related to energy and power systems, with emphasis on the following areas:
Variable energy resource integration
Optimization and stochastic modeling methodologies
Energy storage
Electricity market analysis
Supports multidisciplinary teams in the application of these methods and tools to complex issues in the domains of environmental, water, and energy system analysis.
Prepares reports, papers, and presentations for conferences, workshops, and technical journals.
Supports program development including the preparation of proposals and participating in sponsor interactions.
Applies the models to selected case studies.
Document and publish to our internal software repository.
Supports multidisciplinary teams in the application of these methods and tools to complex issues in the domains of environmental, water, and energy system analysis.
Position Requirements
Recent or soon-to-be completed (typically within the last 0-5 years ) Ph.D. in Engineering, Operations, Computer Science, Mathematics or a related field.
Knowledge of optimization, power systems operations and planning, electricity markets, issues surrounding the integration of variable renewables, & environmental issues.
Experience in statistics & stastical analysis.
Understanding of basic financial & economic principles.
Experience in academic writing & publication.
Ability to be highly motivated and self-starting.
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.
Job Family
Postdoctoral
Job Profile
Postdoctoral Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full timeThe expected hiring range for this position is $70,758.00-$117,925.00.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
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As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
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