Elmhurst Visiting Student - ESIA - Nguyen, Hannah - 3.16.26

Argonne National Laboratory • Lemont, IL

1d

About The Position

This project will develop and validate a Python based AI agent tool that extracts process level and supply chain parameters from scientific and technical literature and organizes them into a structured format suitable for use in GREET. The goal is to create a flexible and reusable AI agent tool that can identify, extract, and structure parameters commonly required for life cycle modeling. The extracted information can support both updates to existing pathways and development of new pathways within GREET. The intern will use Argonne internal large language model tools such as Argo or AskSage as the primary engines for document analysis and data extraction. Education and Experience Requirements The entirety of the appointment must be conducted within the United States. Must be 18 years or older at the time the appointment begins. Applicants must be: ‒ Currently enrolled in undergraduate or graduate studies at an accredited institution ‒ Graduated from an accredited institution within the past 3 months; or ‒ Actively enrolled in a graduate program at an accredited institution

Requirements

• The entirety of the appointment must be conducted within the United States.
• Must be 18 years or older at the time the appointment begins.
• Currently enrolled in undergraduate or graduate studies at an accredited institution
• Graduated from an accredited institution within the past 3 months; or
• Actively enrolled in a graduate program at an accredited institution

Responsibilities

• Develop and validate a Python based AI agent tool that extracts process level and supply chain parameters from scientific and technical literature and organizes them into a structured format suitable for use in GREET.
• Create a flexible and reusable AI agent tool that can identify, extract, and structure parameters commonly required for life cycle modeling.
• Support both updates to existing pathways and development of new pathways within GREET.
• Use Argonne internal large language model tools such as Argo or AskSage as the primary engines for document analysis and data extraction.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees