SULI - ESIA - Czech, Emilia - 2.27.26

Argonne National Laboratory • Lemont, IL

11h

About The Position

This project helps develop data-driven tools to analyze costs, efficiency, and environmental impacts, supporting smarter decisions for U.S. energy planning and policy. We are leveraging Argonne's techno-economic analysis (TEA) models (i)HEVISAM (for EV charging infrastructures) & (ii) HCSAM (to study the production, supply, and utilization of hydrogen, ammonia, methanol, and other emerging energy carriers) which support the U.S. energy dominance. The intern will help implement and improve Python-based TEA models, create a graphical user interface (GUI) for easier data visualization and scenario analysis, and apply machine learning or regression techniques to interpret large datasets. This worksupports ongoing efforts to evaluate the economic feasibility and environmentalimpact of energy systems in collaboration with the U.S. Department of Energy andpartner institutions. Experience with Python programming is highly desirable,including data analysis libraries (pandas, NumPy) and GUI frameworks (Dash).Additionally, familiarity with energy systems, chemical processes, or techno-economic modeling, machine learning or regression methods is preferred.Coursework in engineering or computer science is preferred. Education and Experience Requirements The entirety of the appointment must be conducted within the United States. 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. Must be 18 years or older at the time the appointment begins. Must possess a cumulative GPA of 3.0 on a 4.0 scale. Must be a U.S. citizen or Legal Permanent Resident at the time of application. If accepting an offer, must pass a screening drug test

Requirements

• The entirety of the appointment must be conducted within the United States.
• 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.
• Must be 18 years or older at the time the appointment begins.
• Must possess a cumulative GPA of 3.0 on a 4.0 scale.
• Must be a U.S. citizen or Legal Permanent Resident at the time of application.
• If accepting an offer, must pass a screening drug test

Nice To Haves

• Experience with Python programming is highly desirable,including data analysis libraries (pandas, NumPy) and GUI frameworks (Dash).
• familiarity with energy systems, chemical processes, or techno-economic modeling, machine learning or regression methods is preferred.
• Coursework in engineering or computer science is preferred.

Responsibilities

• implement and improve Python-based TEA models
• create a graphical user interface (GUI) for easier data visualization and scenario analysis
• apply machine learning or regression techniques to interpret large datasets

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed