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 on manufacturing sector energy use modeling, optimization, and analysis, encompassing both supply-side and demand-side technology transformations needed for achieving near zero emissions by 2050, a goal also often referred to as “decarbonization” in the context of climate change mitigation. The candidate would be expected to conduct high-impact research in two primary areas.

[Area 1] Improving the performance of and new capabilities to established energy systems modeling and optimization tool(s) at Argonne: This would entail adapting the in-house industrial decarbonization optimization models to decomposition techniques and/or relevant numerical methods to dramatically reduce time to a feasible solution, parallelization of computations/high-performance computing, and other emerging and novel techniques to improve the efficiency of the models’ pre-processing, optimization, and post-processing steps. The candidate would also be expected to lead, and in some instances, support the development of additional modeling and analysis capabilities such as optimization under uncertainty, multi-objective optimization, statistical analysis and data visualization modules for aiding interpretation of model results, and addition of a graphical user interface for the model(s). The appointee will work with a team of computational scientists and systems engineers at Argonne in this research area.

[Area 2] Developing industrial decarbonization case studies using Argonne’s optimization models: The optimization model(s) in [Area 1] are developed for providing strategic analysis and insights to federal agencies and industry stakeholders to help them make decisions and investments, specifically around decarbonization of the U.S. industry sector. The appointee will leverage their expertise in systems modeling to develop high-fidelity decarbonization roadmapping models for energy and emissions-intensive industries, including iron & steel, cement, chemicals, food & beverage, refining, glass, and aluminum manufacturing. The appointee will work a team of subject matter experts from different DOE National Laboratories in each of these manufacturing sub-sectors in developing the model and analysis framework.

Candidates must demonstrate a strong technical background in mathematical optimization and should preferably have some experience developing energy systems models and/or working on integrated assessment models. 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 sponsors and work in large interdisciplinary teams.

Position Requirements

• Ph.D. in industrial and systems engineering, operations research/management science, chemical/mechanical engineering or related fields.
• Experience in command of optimization, statistics, and general engineering fundamentals.
• Experience developing mathematical or computational models for simulation and optimization of energy/economic systems in Julia, Python, R, or other scientific programming languages.
• Experience developing software packages, tools, and data sets for public use.
• Ability to synthesize effective data visualizations to communicate results from complex data analyses.
• 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, and emissions.
• Demonstrable expertise in systems-level thinking that draws from several scientific disciplines including engineering, economics, and environmental science.
• Familiarity with life cycle analysis and techno-economic analysis, particularly in the context of energy and industrial technologies.
• Experience working in multidisciplinary research environments.
• 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.

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