Graduate Intern – AI/ML for Cybersecurity

Job not on LinkedIn

🕒 October 15

⛰️ Colorado – Remote

⛰️ Colorado – Remote

💵 $51.2k - $81.9k / year

👨‍🎓 Internship

⚪️ Entry-level

👮‍♂️ Cybersecurity / Security Engineer

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Advanced Energy Systems - Colorado School of Mines & NLR

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2019

📚 Education

⚡ Energy

🔬 Science

Education • Energy • Science

Advanced Energy Systems - Colorado School of Mines & NLR is an interdisciplinary graduate engineering program created through a partnership between the Colorado School of Mines and the National Laboratory of the Rockies (NLR). The program educates and trains master’s and doctoral researchers to address the technical, economic, and environmental challenges of modern energy infrastructure, emphasizing secure, resilient, and adaptive systems. Students collaborate with faculty and NLR researchers, use shared state-of-the-art facilities, work with industry, government, and nonprofit partners, and prepare for careers solving large-scale energy-system problems.

📋 Description

• Conduct hands-on research at the intersection of machine learning, statistics, and critical energy infrastructure security • Enhance the reliability, transparency, and operator-readiness of AI-driven cybersecurity tools for power grid substations and physical assets • Design and implement explainable AI methods, including attribution maps, rule extraction, and root-cause analyses • Apply statistical techniques such as conformal prediction, Bayesian neural networks, and ensemble methods to quantify model confidence and predictive uncertainty in real time • Analyze cyber-physical power system security datasets, including 9-Bus system baselines and cyber-physical anomaly runs • Explore machine learning safety techniques, including model steering, for predictable behavior under distribution shifts or input corruptions • Support visualization and alert design for explainability and confidence metrics and alert prioritization • Partner with cybersecurity researchers and AI development teams • Integrate explainability modules, document results, and compile deployment guidelines for reliable AI models

🎯 Requirements

• Minimum cumulative GPA of 3.0 • Undergraduate applicants must be enrolled full-time in a bachelor's degree program from an accredited institution • Post-undergraduate applicants must have earned a bachelor's degree within the past 12 months • Graduate applicants must be enrolled full-time in a master's degree program from an accredited institution • Post-graduate applicants must have earned a master's degree within the past 12 months • Graduate + PhD applicants must have completed a master's degree and be enrolled as a PhD student from an accredited institution • Currently pursuing or completed a Bachelor's, Master's, or Ph.D. in Computer Science, Cybersecurity, Electrical Engineering, AI, Applied Mathematics, or Statistics • Must meet educational requirements prior to employment start date • Applicants must upload official or unofficial school transcripts • Letter of recommendation required if selected • 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 • Ability to obtain and maintain a federal Personal Identity Verification (PIV) card for assignments extending beyond six months, including a favorable background investigation • Must pass a pre-employment drug test, which may include marijuana unless prohibited by state or local law • Must submit an application, cover letter, and resume for each position • Preferred: active research/publications in specified top-tier conferences • Preferred: experience with Captum, SHAP, LIME, and uncertainty calibration methods • Preferred: familiarity with multi-sensor data fusion, power systems modeling, or grid anomaly detection • Preferred: contributions to open-source AI transparency, reliability, or security libraries

🏖️ Benefits

• Medical, dental, and vision insurance • 403(b) Employee Savings Plan with employer match • Sick leave where required by law • Potential eligibility for performance-, merit-, and achievement-based monetary awards • Potential eligibility for relocation expense reimbursement • Robust professional development opportunities • Competitive benefits package designed to support career and well-being

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