Research Aide - TAPS - Salvador, Isaac - 2.18.2026

Argonne National Laboratory•Lemont, IL

1d•$27 - $40

About The Position

Developing next-generation transportation agent-based models requires robust data foundations and advanced statistical methods to represent complex travel behavior and system dynamics. This project focuses on data analysis in support of statistical and AI-based modeling within the POLARIS development framework. The student will prepare, curate, and analyze large-scale travel, network, and behavioral datasets to support the estimation, validation, and testing of machine learning and statistical components embedded in POLARIS. Responsibilities include feature engineering for behavioral models, exploratory data analysis to identify latent patterns in agent decision-making, and supporting model calibration and performance evaluation to improve predictive accuracy and computational efficiency of large-scale transportation simulations. 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. If accepting an offer, must pass a screening drug test Must complete a satisfactory background check

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; 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.
If accepting an offer, must pass a screening drug test
Must complete a satisfactory background check

Responsibilities

feature engineering for behavioral models
exploratory data analysis to identify latent patterns in agent decision-making
supporting model calibration and performance evaluation to improve predictive accuracy and computational efficiency of large-scale transportation simulations

Benefits

comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
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.
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.
Please be advised that 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.