Digital Twin Intern

⚛️
Advance the Future of Nuclear Energy with INL!

Idaho National Laboratory (INL) is seeking a graduate student in Nuclear Engineering (or a closely related field) for a Summer 2026 internship to help develop a discrepancy checking and diagnosis tool for a digital‑twin–based supervisory control system
. This is a hands‑on research opportunity to apply AI and machine learning methods to next‑generation energy systems.

• Integrate active learning
  , reinforcement learning
  , and multi‑agent AI systems into a digital twin (DT) framework.
• Design and implement methods for discrepancy detection and diagnosis within a DT‑based supervisory control loop.
• Apply verification, validation, and uncertainty quantification (VVUQ) to evaluate model fidelity and decision robustness.
• Analyze simulation and sensor data, develop ML models in Python
  , and contribute to technical reports and publications
  .

Enrolled full time in a Ph.D. program in Nuclear Engineering or a closely related field.

Coursework or experience in modeling & simulation
, machine learning
, verification & validation
, and uncertainty quantification
.

Familiarity with Python and strong analytical skills.

Minimum 3.0 GPA and authorization to work in the U.S. (including CPT/OPT).

• Experience with reinforcement learning
  , active learning
  , digital twins
  , or advanced control systems
  .
• Comfort with time‑series/sensor data and data–model discrepancy analysis
  .
• Excellent written and verbal communication skills and a passion for collaborative research.

📍
Onsite at INL – Idaho Falls,
🗓️
Summer 2026 | Flexible start date
🕘 9x80 schedule (every other Friday off)
🎓 Doctoral-level internship | Course credit may be available

Join us and help shape the future of AI‑driven nuclear control systems through cutting‑edge digital twin research.