The Industrial Technologies Group within the Energy Systems and Infrastructure Assessment (ESIA) Division at Argonne National Laboratory seeks a highly qualified Postdoctoral Appointee to conduct applied research on AI-driven and AI-enhanced industrial energy systems optimization modeling, material flow analysis, and supply chain analysis of industrial commodities and critical materials.

The successful candidate will contribute to Argonne’s industrial capacity planning, logistics optimization, and supply chain analysis models and apply these tools to support high-impact research on resilient, competitive, and energy-efficient U.S. manufacturing systems. The appointee will be expected to lead core model development and as needed, help expand capabilities in co-optimization of industrial end-use and energy supply systems, multi-objective and stochastic optimization, advanced statistical analysis, and data visualization.

This position offers the opportunity to work with ...