SULI - AMD - Behrens, Jan - 6.17.26

Argonne National Laboratory • Lemont, IL

4d • Onsite

About The Position

This internship offers the chance to contribute to a cutting-edge research project with Argonne’s Extreme Materials and Interfaces group. The focus is on developing an AI-guided discovery platform for multifunctional coatings in extreme environments. As an intern, you would join a multidisciplinary team working to build and validate a human-supervised, AI-driven workflow that accelerates the design of refractory high-entropy alloy coatings-materials critical for applications facing extreme temperatures, mechanical stress, and corrosive conditions. The project integrates literature review, data curation, active learning, Multiphysics simulation, and advanced experimental validation using synchrotron x-ray techniques. You’ll gain hands-on experience in scientific data analysis, machine learning, and materials characterization, and contribute to the creation of microstructure-to-property maps that can transform how advanced coatings are designed for the energy, manufacturing, and transportation sectors. This opportunity is ideal for students interested in materials science, mechanical engineering, computational modeling, and artificial intelligence.

Requirements

• 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

• Interest in materials science, mechanical engineering, computational modeling, and artificial intelligence.

Responsibilities

• Contribute to a cutting-edge research project with Argonne’s Extreme Materials and Interfaces group.
• Develop an AI-guided discovery platform for multifunctional coatings in extreme environments.
• Build and validate a human-supervised, AI-driven workflow that accelerates the design of refractory high-entropy alloy coatings.
• Integrate literature review, data curation, active learning, Multiphysics simulation, and advanced experimental validation using synchrotron x-ray techniques.
• Gain hands-on experience in scientific data analysis, machine learning, and materials characterization.
• Contribute to the creation of microstructure-to-property maps that can transform how advanced coatings are designed for the energy, manufacturing, and transportation sectors.

What This Job Offers

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