Research Aide - NSE - Ouyang, Haoran - 3.16.2026
About The Position
The main task during the internship is to improve the estimation accuracy ofequivalence parameters for Griffin low-order solvers using AI/ML techniques.The equivalence parameters (superhomogenization and discontinuity factors)vary with reactor core state conditions and can change dramatically with controldrum rotations in microreactors. An AI/ML approach is well suited to reducingtabulation memory requirements, regularizing the variation of equivalenceparameters, and enhancing prediction accuracy across a wide operational space.In addition, AI/ML techniques may be used to estimate local fine-group spectra,enabling faster online group condensation in Griffin high-order transportcalculations with online cross-section generation (SSAPI). This capability is expected to reduce computational cost while maintaining high-order accuracy. Verification tests for the proposed tasks will be conducted using representative gas-cooled microreactor problems. The analysis results and developmentoutcomes will be documented in a technical report.
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
Benefits
- comprehensive benefits are part of the total rewards package.
- Click here to view Argonne employee benefits!
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
No Education Listed
Number of Employees
1,001-5,000 employees
