SULI - XSD - Gopinathan, Ashwin - 2.27.26

Argonne National Laboratory • Lemont, IL

18h

About The Position

The student researcher will contribute to developing a multimodal foundation model for materials characterization that uses X-ray Absorption Spectroscopy (XAS) as a central modality to connect diverse materials information including atomic structures, spectroscopic data, and textual metadata. They will assemble and preprocess large-scale XAS datasets, design neural architectures to integrate heterogeneous data types, and train multimodal models to learn shared representations across different data modalities. The work also involves developing validation tasks and downstream applications, such as suggesting candidate atomic structures for spectral fitting. This project aims to create AI tools that enable autonomous, high-throughput XAS analysis while addressing a key bottleneck in materials informatics: the limited availability of scalable and interpretable multimodal models for materials characterization. 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, candidates may be required to complete pre-employment drug testing based on appointment length. All students remain subject to applicable drug testing policies.

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, candidates may be required to complete pre-employment drug testing based on appointment length.

Responsibilities

• Assemble and preprocess large-scale XAS datasets
• Design neural architectures to integrate heterogeneous data types
• Train multimodal models to learn shared representations across different data modalities
• Develop validation tasks and downstream applications, such as suggesting candidate atomic structures for spectral fitting

What This Job Offers

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