Graduate Intern – Power Data Analysis for AI Data Centers

Location: Golden, CO

Posting Title

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Location

CO - Golden

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Position Type

Intern (Fixed Term)

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Hours Per Week

40

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Working at NLR

NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.

Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.

At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.

The Digital Twins and Scalable Workflows group in NLR’s Computational Science Center has an opening for a graduate student researcher in data center power analytics, with an emphasis on the electrical behavior of AI workloads. AI is driving rapid growth in data center electricity demand, and the sub-second power swings of GPU workloads are a growing concern for grid stability. This project measures the electrical power of GPU racks on NLR’s Kestrel supercomputer while AI training, inference, and agentic workloads run, and uses those measurements to build models that predict realistic power behavior for workloads that haven’t been measured.

The researcher will be the project’s eyes on the data: reviewing the power measurements from every experiment, identifying anomalies and tracing their causes through system telemetry and profiling data, and labeling power ramps and other critical events. The researcher will also build an automated event detector, trained and evaluated on their own labeled data, that flags ramps and anomalies in new measurements.

We are looking for a curious, detail-oriented researcher with strong data analysis skills and an interest in energy, computing, and the grid. The successful candidate will work closely with NLR researchers in high-performance computing, power systems, and data center operations, and will have the opportunity to present and publish their work.

Responsibilities include

• Review power measurements from AI workload experiments for anomalies and data quality issues, using an interactive visualization workbench.
• Hand-label power ramps, load steps, and other critical events, and identify regions that exemplify characteristic workload behavior, following a documented labeling protocol.
• Investigate unexplained behavior by correlating power measurements with GPU telemetry, profiling data, job logs, and system configuration, and document the findings.
• Design, build, and evaluate an automated detector for power ramps and anomalies, trained and tested on labeled data.
• Present results and contribute to technical reports, papers, and conference presentations.
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Basic Qualifications

• Minimum of a 3.0 cumulative grade point average.
• Undergraduate: Must be enrolled as a full-time student in a bachelor’s degree program from an accredited institution.
• Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year.
• Graduate: Must be enrolled as a full-time student in a master’s degree program from an accredited institution.
• Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year.
• Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution.

Please Note

• Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process.
• If selected for position, a letter of recommendation will be required as part of the hiring process.
• Must meet educational requirements prior to employment start date.
• Must meet educational requirements prior to employment start date.

Additional Required Qualifications

Preferred Qualifications

• Careful attention to detail, and the ability to follow and help refine a structured review process.
• Excellent written and verbal communication skills, including clear documentation of findings.
• Ability to work independently and to raise questions early.
• Experience analyzing time-series or signal data (for example, spectral analysis or event detection).
• Familiarity with GPU computing, AI/ML workloads, or HPC systems (for example, Slurm).
• Programming experience in Python for data analysis.
• Experience with machine learning for classification or detection.
• Background in power systems or electrical measurements.
• Experience with data labeling, annotation, or data quality review.
• Additional Locations: Remote Site