Graduate Intern - AI-Assisted Autonomous Electron Microscopy

Posting Title

Graduate Intern – AI-Assisted Autonomous Electron Microscopy

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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.

Job Description

The DTSW at the National Laboratory of the Rockies (NLR) has an opening for a graduate intern to contribute to a cutting-edge project at the intersection of autonomous instrumentation, computer vision, and large language models (LLMs) for materials characterization.

This project offers a unique opportunity to advance the "self-driving" capabilities of electron microscopes by codifying expert experimental protocols into robust, executable algorithms. The intern will develop Python-based scripting routines to automate image acquisition, elemental analysis, and real-time experimental adjustments — enabling intelligent, adaptive operation across a range of materials relevant to energy, microelectronics, and power technologies.

Working alongside experienced researchers in materials science and data science, the intern will integrate LLMs to enhance natural language processing of microscope commands, automate reporting workflows, and guide experimental decision-making. The project further explores how machine learning and computer vision can enable autonomous region-of-interest detection, defect identification, and compositional mapping at the nanoscale.

Responsibilities include:

• Develop and validate automated Python scripting routines for electron microscope control, including image acquisition, stage manipulation, and adaptive data collection workflows.
• Build and test computer vision pipelines (e.g., segmentation, defect detection) for real-time analysis of scanning transmission electron microscopy (STEM) and scanning electron microscopy (SEM) images.
• Integrate large language model (LLM) interfaces for natural language command processing, automated report generation, and AI-guided experimental planning.
• Apply machine learning methods to grain analysis, particle characterization, and compositional mapping using STEM, SEM, and associated spectroscopic datasets.
• Collaborate with research staff to evaluate and iterate on autonomous workflows for throughput, reproducibility, and scientific fidelity.
• Document code, prepare technical summaries, and contribute to reports and publications as appropriate.

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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

• Proficiency in Python programming, including experience with scientific libraries (NumPy, SciPy, Pandas, scikit-image, OpenCV, or equivalent).
• Experience applying machine learning or computer vision methods to image-based data (segmentation, classification, detection, or related tasks).
• Strong analytical and problem-solving skills, with attention to precision in experimental or computational workflows.
• Excellent written and verbal communication skills; ability to document and present technical work clearly.

Preferred Qualifications:

• Prior hands-on experience analyzing microscopy images (SEM, TEM, optical, or equivalent), including grain analysis, particle segmentation, or defect characterization.
• Familiarity with large language model (LLM) APIs or frameworks (e.g., LangChain, OpenAI API, Hugging Face Transformers).
• Experience working with industrial or laboratory datasets in a research or applied context.
• Background in computational mathematics, data science, or a related quantitative field.
• Coursework or experience in materials characterization, electron microscopy, or related experimental methods is a plus but not required.

Preferred Qualifications

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Job Application Submission Window

The anticipated closing window for application submission is up to 30 days and may be extended as needed.

Annual Salary Range (based on full-time 40 hours per week)

Job Profile: / Annual Salary Range: $44,500 - $71,200

NLR takes into consideration a candidate’s education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions.

Benefits Summary

Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.

* Based on eligibility rules

Badging Requirement

NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.

Drug Free Workplace

NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.

If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.

Submission Guidelines

Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.

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Equal Opportunity Employer

All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

Reasonable Accommodations

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