Predoctoral Appointee - Techno-Economic Analysis

Support tool development and data management for the Techno-Economic Analysis Group in Argonne's Energy Systems and Infrastructure Analysis Division, chiefly the Energy Systems Techno-Economic Evaluation Model (ESTEEM), which assesses the technical, economic and environmental benefits of producing, transporting and delivering commodities across the industrial, transportation and power sectors. The appointee converts Excel-based techno-economic models into tested, modular Python for a centralised modelling platform, helps shape its architecture and interfaces, maintains and validates technical datasets, and prepares documentation and progress summaries.

A recent or soon-to-be-completed master's degree in engineering, computer science, data science, applied mathematics, economics or a related field; proficient modular Python with pandas and NumPy; experience with Excel-based models, software-development practice and database concepts; quantitative skills to reconcile model results. Experience converting engineering or economic models to Python, SQL, Git-based development and techno-economic concepts such as levelised costs is preferred. On-site presence at the Lemont campus is required. Stated hiring range: USD 58,297–97,161.