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.

As part of INL’s cutting-edge research team, you’ll:
🤖 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.

Minimum Requirements:

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).

Preferred Qualifications:

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, ID
🗓️ 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.