Research Aide– CPS – Xia, Bin– 4.20.26

Argonne National Laboratory • Lemont, IL

2d

About The Position

Bin Xia will work on developing and deploying a multi-modal foundation model for astrophysical galaxy data of over 100 million synthetic galaxies. The project focuses on building a unified model that connects simulation-based and observation-based galaxy properties, enabling prediction across modalities such as photometry, spectra, redshift, stellar mass, and star formation history. He will also help link these foundation models with agentic AI systems for cosmology, supporting more flexible scientific analysis and discovery.

Requirements

• The entirety of the appointment must be conducted within the United States
• 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
• 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
• Candidates may be required to complete pre-employment drug testing based on appointment length
• All students remain subject to applicable drug testing policies
• Must complete a satisfactory background check
• All Argonne offers for appointments in the student employment category are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis
• Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements
• Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment

Responsibilities

• Developing and deploying a multi-modal foundation model for astrophysical galaxy data of over 100 million synthetic galaxies
• Building a unified model that connects simulation-based and observation-based galaxy properties, enabling prediction across modalities such as photometry, spectra, redshift, stellar mass, and star formation history
• Help link these foundation models with agentic AI systems for cosmology, supporting more flexible scientific analysis and discovery

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees