SULI - MCS - Pandya, Anagh - 2.24.26.

Argonne National Laboratory • Lemont, IL

9h

About The Position

Artificial Intelligence techniques have been increasingly adopted by the plasma and fusion science to address problems like plasma reconstruction, surrogate modeling, and tokamak/stellarator optimization. A key focus in sustained fusion research is the prediction and mitigation of Edge-Localized-Modes (ELMs), instabilities that occur in short, periodic bursts and can cause erosion to the tokamak vessel wall. Recent research has demonstrated the power of neural networks in approximating continuous functions. In this project, we will look at several time series foundation models (e.g. CHRONOS, TimerXL etc) that enable combining 0d, 1d and 2d signals from DIII-D tokamak plasmas. The focus of this study will be to leverage the Retrieval Augmented Generation (RAG) and finetuning methods for prediction and uncertainty quantification of ELMs using fluctuation diagnostics from DIII-D tokamak reactor.

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, must pass a screening drug test.

What This Job Offers

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