About the role#
This internship focuses on the intersection of machine learning, statistics, and critical energy infrastructure security. You will work on enhancing the reliability, transparency, and operator-readiness of AI-driven cybersecurity tools used to secure power grid substations and physical assets. The research emphasizes explainability and robust uncertainty bounds to ensure these tools are effective for system administrators.
What you'll do#
- Design and implement XAI methods to make complex ML models transparent and auditable.
- Apply statistical techniques to quantify model confidence and measure predictive uncertainty in real-time.
- Analyze cyber-physical power system security datasets to extract feature patterns and validate anomaly detection model behavior.
- Explore machine learning safety techniques, including model steering, to ensure grid security models behave predictably.
- Support research into visualization methods and alert design that present explainability and confidence metrics clearly to operators.
- Partner with cybersecurity researchers and AI development teams to integrate explainability modules, document results, and compile guidelines.
What you'll need#
- Currently pursuing or completed a Bachelor’s, Master’s, or Ph.D. in Computer Science, Cybersecurity, Electrical Engineering, AI, Applied Mathematics, or Statistics.
- Minimum 3.0 cumulative GPA.
- Strong proficiency in Python.
- Hands-on experience with PyTorch, TensorFlow, or Hugging Face.
- Substantial coursework or project experience in Explainable AI (XAI), machine learning safety, confidence calibration, or statistical uncertainty modeling.
- Practical experience working with Large Language Models (LLMs), Foundation Models, or other complex deep neural networks.
- Must be enrolled as a full-time student or have graduated within the past 12 months.
Location & details#
- Location: Golden, Colorado.
- Term: 10 to 12 weeks, rolling.
- Status: Full-time, paid.
- Note: This position is subject to Department of Energy access restrictions. All candidates must be able to obtain and maintain a federal Personal Identity Verification card, which includes a background investigation. Employment is conditional on passing a pre-employment drug test.
About National Renewable Energy Laboratory
The National Renewable Energy Laboratory operates as the primary national laboratory for the United States Department of Energy focused on energy systems research. Founded in 1977, the organization conducts research in energy efficiency, basic science, and energy security. It maintains a staff of approximately 3,751 employees. The laboratory is based in Golden, Colorado.
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