The Decision and Infrastructure Sciences (DIS) Division is seeking a highly motivated Energy Economist. The position will support DIS Division with economic and supply chain modeling and analysis, with a focus on critical materials, supply chains, and manufacturing associated with energy sector industrial base (ESIB) technologies and U.S. decarbonization goals.
In this role you will:
Contribute to research and analysis and model development to aid decision-making around topics related to improving the domestic and global resilience of supply chains for technologies vital to clean energy and decarbonization of the U.S. economy.
Contribute technical and policy insights to decision makers in areas related to manufacturing and energy supply chains and related technologies.
Provide analysis to understand and inform stakeholders of the economic, environmental, and social justice impacts of deploying various strategies to mitigate risks to achieving the nation’s decarbonization goals.
Provide research that builds on existing datasets, analysis, and computational models developed by the Argonne, DOE national laboratory collaborators, and federal sponsor teams.
Contribute to the development and application of analytical approaches, compilation of results, report preparation, publications, and documentation that evaluate U.S. decarbonization goals and ESIB technology supply chains and quantify impacts of U.S. policies.
Identify data sources and manage data resources as required for the development of complex system models.
Develop new analytic tools and datasets.
Prepare briefings and reports on analysis, methodology, and results.
Collaborate with researchers from other DOE Nationals Laboratories and contribute to interdisciplinary teams.
Receive a supportive and enabling environment to develop research projects, grow research collaborations, communicate impactful research outcomes in peer-reviewed journals, and support other related projects within the team’s portfolio.
Strengthen career path opportunities by expanding technological skills, developing independent research capabilities, and building professional skills such as communication, networking and leadership.
Position Requirements
Strong technical background in economics, operations research, public policy, or another relevant field and a strong desire to apply that background to the mineral and energy sectors.
Knowledge of economic principles and aspects associated with mineral and energy sector supply chains.
A record of scholarly work in economic and/or supply chain analysis, criticality, computational modeling, scenario analysis, or policy analysis or strong, transferrable industry experience.
Skilled oral and written communication skills in scientific and engineering field.
Ability to integrate diverse knowledge, methods, and perspectives to drive analysis and innovation.
Ability to support research projects, work independently, establish collaborations, travel to meetings, and work effectively with members of multidisciplinary research teams.
Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
Ability to make our laboratory a safe, welcoming, inclusive, and accessible environment where all can thrive.
Preferred Requirements
Specialized knowledge of metals and materials markets and supply chains or the manufacturing of clean energy technologies.
Experience with economic analysis techniques (econometrics, input-output models, optimization, cost modeling, computational modeling, etc.).
Specialized experience evaluating specific energy technologies and/or critical materials.
Skill in organizational and time management, with careful attention to detail and the ability to handle multiple stakeholders and priorities and experience working independently under time constraints to meet critical deadlines.
Experience or familiarity with mineral, manufacturing, or supply chain policy.
Experience with manufacturing or ESIB supply chain analysis.
Familiarity with techno-economic and life cycle analysis.
Experience with modern scientific programming languages (e.g., R, Python, Java) and/or ability to work with widely accepted statistical analysis software (e.g., Stata).
Ability to develop and synthesize visualizations to effectively communicate analysis results.
Some experience with optimization, operations research, or other computational modeling techniques, such as agent-based modeling, general equilibrium modeling, etc.
Selected candidate will be required to obtain and maintain a clearance and must be a U.S. citizen. Please see http://www.state.gov/m/ds/clearances/c10978.htm for more information about requirements for obtaining a security clearance process.
This level of knowledge is typically achieved through a formal education in economics, mathematics, operations research, systems engineering, environmental science/engineering, or any relevant engineering and computational sciences field. The selected candidate will be placed in the appropriate level (RD1 or RD2) depending upon depth and breadth of relevant knowledge, skills, and experience brought to the position. The requirements for the desired levels are as follows:
RD1 Level: Bachelor’s or Master’s and 0+ years, or equivalent.
RD2 Level: Bachelor’s and 5+ years; Master’s and 3+ years; Doctorate and 0+ years, or equivalent.
Job Family
Research Development (RD)
Job Profile
Social Science/Law 1
Worker Type
Regular
Time Type
Full 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.
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