Elmhurst Visiting Student - ESIA - Sara, Mashia - 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 Job Family Visiting Student Undergraduate Job Profile Visiting Student - Undergraduate Worker Type Contingent Worker Time Type Full time Scheduled Weekly Hours 40 EEO Information As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law. Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

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
• 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
• Organize extracted information into a structured format suitable for use in GREET
• Identify, extract, and structure parameters commonly required for life cycle modeling
• Support 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