The Applied Materials Division (AMD) at Argonne National Laboratory conducts applied research to develop sustainable innovative technologies to improve the efficiency of resource and energy utilization; to minimize our dependence on imported energy; and to enhance our national security. A Sustainable Materials & Processes Data Modeling and Analysis Group Leader position is now open for an energetic candidate with leadership skills and experience in techno-economic analysis (TEA) and life cycle analysis (LCA). In this leadership role, the successful candidate will collaborate closely with the department manager, division director, project/thought leaders, and a dedicated team of experts to support the Sustainable Materials and Processes Department in pursuing AMDs missions and strategies. The successful candidate will act as Principal Investigator to manage and expand the portfolio of research projects by interacting with DOE program managers, and collaborating across Argonne, national laboratories, universities, and industry. The successful candidate will work closely with project leads to plan and execute projects to deliver to stakeholders, including managing budgets and financial responsibilities. The successful candidate will also support DEIA-related activities and outreach at the lab and will promote project collaboration with other groups at Argonne across divisions. More specifically, this candidate will play a key role in developing and expanding capabilities for data modeling and analysis in the Sustainable Materials and Processes Department. The focus of the group is modeling and analysis of recycling and other decarbonization and sustainability focused materials, processes, and technologies. A good knowledge of conceptual process design, simulation, and optimization, process integration and intensification, and energy system optimization is of importance. The candidate should be familiar with databases, tools, and methodologies relevant to TEA and LCA. The successful candidate will lead a team that uses the EverGreen and IMPACT models, as well as others, to assess and improve advanced research and concepts going on in the lab and out in the field. **Position Requirements**
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