The Buildings & Industry Group within the Energy Systems and Infrastructure Analysis (ESIA) Division at Argonne is seeking to hire a postdoctoral appointee to conduct research and modeling-based analysis of (1) decarbonization pathways for energy- and emissions-intensive industries and (2) material circularity pathways in a low-carbon future.
The candidate would conduct research across multiple DOE-sponsored projects that would entail developing analysis insights critical to strategic technology RDD&D investments at the federal and state levels. Such analyses would be rooted in transparent, repeatable, and credible analysis of industrial technologies and technology systems that employ a range of tools including process and thermodynamic modeling, life cycle assessment, techno-economic analysis, supply chain and materials flow analysis, and agent-based modeling. The candidate would build on established modeling tools at Argonne in each of the modeling/analysis areas, but there may be opportunities for additional model/tool development based on sponsor needs and the candidate’s area of expertise. Some potential application areas include low-carbon fuels and feedstocks, electrified manufacturing processes, carbon capture & storage, plastics recycling and circularity, and critical materials supply chains.
Candidates should demonstrate a strong technical background in manufacturing engineering and industrial ecology and should preferably have some experience working on interdisciplinary projects. Proficiency in oral communication and technical writing, as demonstrated by the candidate’s peer-reviewed publications and presentations, is necessary for this position given the need for the appointee to directly interface with various federal and state government sponsors and team members from other national laboratories.
Position Requirements
Ph.D. in mechanical, industrial, chemical engineering or related fields.
Demonstrable expertise in systems-level thinking that draws from several scientific disciplines including engineering, economics, and environmental science.
Experience developing mathematical or computational models for simulation and optimization of energy/economic systems in ASPEN Plus® and/or Julia, Python, R, Java, or other scientific programming languages.
Experience working with life cycle assessment tools such as GREET®, OpenLCA, SimaPro®, GaBi®, or similar.
Skilled oral and written communication skills as evidenced by a strong record in academic publications and conference presentations.
Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
Ability to make our laboratory a safe, welcoming, inclusive, and accessible environment where all can thrive.
Preferred Qualifications:
Knowledge of conventional and next-generation energy and manufacturing technologies, and their environmental impacts including energy use, water use, emissions, and resource depletion.
Coursework and some project experience in application of mathematical optimization, statistics, or machine learning to engineering problems.
Experience developing software packages, tools, and data sets for public use.
Ability to synthesize effective data visualizations to communicate results from complex data analyses.
Ability to think strategically, use independent judgment, and exercise thought leadership.
Ability to develop evidence-based policy insights in science and technology.
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 job incumbent. Consequently, job incumbent may be required to perform other duties as assigned.
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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