Postdoctoral Appointee: Researcher
Job posting number: #7192422 (Ref:416790)
Posted: November 10, 2023
The Systems Assessment Center (SAC) of Argonne National Laboratory (ANL) has been conducting assessments of advanced vehicle technologies and new transportation fuels over the last 30 years. It has developed the GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model for estimating energy use, emissions, and water consumption on a life-cycle basis for conventional and new vehicle/fuel systems (see https://greet.anl.gov/ for details). The GREET model has more than 55,000 registered users worldwide, including academia, industry, and regulatory agencies. Besides, the Center has examined economic and cost effects of new vehicle technologies, infrastructure buildup, and transportation energy. The SAC has been working closely with auto, rail, and energy industries, universities, and governmental agencies to evaluate energy, environmental, and economic impacts of advanced vehicle technologies and new transportation fuels.
The SAC continues to assess conventional and advanced fuels production technologies for their energy, environmental, and economic effects. A Postdoctoral Appointee position is now open for a candidate with expertise and experience in energy economics of rail and other transportation modes.
The candidate will analyze energy systems for rail and other offroad applications to evaluate their decarbonization potential, the associated cost, and the potential cost/benefits tradeoffs. In particular, the candidate will investigate decarbonization alternatives for the US freight and passenger rail industry and intermodal systems, considering economic, environmental, and operational aspects. The candidate will compare battery-electric and hydrogen fuel-cell locomotives, as well as biofuels, through abatement cost analysis leveraging ANL’s GREET, HDSAM, HEVISAM and other tools.
Additionally, the candidate will develop models building upon existing comprehensive frameworks to evaluate the financial, environmental, and operational implications of different decarbonization scenarios for rail and intermodal systems at national level. This will include gathering and analyzing data on acquisition costs, maintenance expenses, fuel consumption, emissions, market penetration, and other factors influencing the total cost of ownership. In this role, the candidate will collaborate with cross-function teams, including engineers, economists, and policy experts, to provide insights and recommendations for quantifying vehicle total cost of ownership. Research findings will be shared and disseminated through technical reports, presentations, and peer-reviewed publications, contributing to the knowledge base and intellectual leadership in the field.
Ph.D. degree in transportation, engineering, environmental, economics, or a related field, and be familiar with energy and environmental impacts of transportation systems, modes, and vehicle/fuel technologies.
Experience with life-cycle analysis (LCA) and tecno-economic analysis (TEA) of conventional and alternate powertrain and fuels.
Experience with emerging technologies (such as connected and automated vehicles, shared mobility, etc.) and alternative fuels likely to be used in transportation systems.
Experience with computer programming (in Java, Python, or a similar language), MS Excel VBA, and other relevant software.
Experience with use of GIS
Skilled in oral and written communications and presentations at all levels of the organization.
Ability to work on cross-cutting issues in inter-disciplinary settings and time management in a team environment.
A successful candidate must have the ability to embody Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
Knowledge of various aspects of advanced rail propulsion systems and fueling technologies, including current and candidate fuels used or likely to be used in rail systems.
Knowledge of cross-sectoral (transportation, industry, commercial, etc.) energy models.
Experience with intermodal operation and logistics.
Experience with system modeling methodologies such as agent-based modeling/simulation.
Experience with various databases and analytical models and experience in analyzing large data sets.
This position description documents the general nature and level of work but is not intended to be a comprehensive list of all activities, duties and responsibilities required of the job incumbent. Consequently, the job incumbent may be required to perform other duties as assigned.
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
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