Visiting Student-Subcontractor - MCS - Shah, Ashka - 6.16.26.

Argonne National Laboratory • Lemont, IL

15h • Onsite

About The Position

This project aims to finish a novel methodology for modeling the context (e.g., environmental stress, disease state, cell state) from which data is sampled, in a causal graph. This enables learning from data across contexts (e.g., combining data across radiation levels or cell-types) yielding a representation that is context-aware that can answer broader questions such as identifying circuits linked to regulatory robustness, and pinpointing key genes for therapeutic targeting. Validation experiments and other computational experiments will be performed to finalize publication.

Requirements

• The entirety of the appointment must be conducted within the United States.
• Must be 18 years or older at the time the appointment begins.
• 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.

What This Job Offers

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