Graduate Intern

About the Role

The MICRO Research Group at the National Laboratory of the Rockies (NLR) seeks a B.S. - graduate intern to support cutting-edge work in focused ion beam (FIB) and plasma FIB (PFIB) instrumentation, with a focus on an autonomous laser-integrated PFIB platform. This role involves operating and advancing the platform, assisting with maintenance, calibration, and scripting workflows to enhance autonomous capabilities. Work will draw on principles from materials science, physics, and chemistry for characterization and sample preparation, including time-sensitive customer assignments requiring documentation and reporting. The intern will develop and validate computer vision pipelines for automated site identification, sample quality assessment, and adaptive ion beam milling strategies. Integration of foundation models and large language models (LLMs) for instrument feedback interpretation and autonomous decision-making is an area of active development.

Key Responsibilities

• Assist with maintenance, calibration, and performance validation of FIB, PFIB, and laser PFIB instruments, following established procedures and safety protocols.
• Develop and test Python-based instrument scripting and automation routines for ion beam control, image acquisition, and adaptive workflow execution.
• Build and validate computer vision pipelines — including semantic segmentation models — for real-time site identification, feature detection, and sample quality assessment during FIB/PFIB operations.
• Support time-sensitive customer characterization assignments, including sample preparation, data collection, and preparation of concise technical reports on short turnaround.
• Explore integration of foundation models and large language models (LLMs) for natural language instrument interfacing, automated reporting, and AI-guided experimental decision-making.
• Collaborate with multidisciplinary staff across materials science, physics, chemistry, and engineering; document methods and contribute to internal reports and peer-reviewed publications.

Requirements & Tech Stack

• 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.
• Onsite work, 30–40 hours per week for at least 6 months, with opportunity to extend.
• Must meet educational requirements prior to employment start date.

Qualifications

• Strong background in materials science, physics, chemistry, engineering, or a closely related discipline at the master’s level.
• Excellent written and verbal communication skills; demonstrated ability to produce clear technical documentation and meet reporting deadlines.
• Ability to work effectively in diverse, multidisciplinary research teams.

Preferred Qualifications

• Prior experience with FIB, PFIB, SEM, TEM, or related electron/ion beam instrumentation, including operation, maintenance, or scripting.
• Proficiency in Python, including scripting for instrument control, data acquisition, or image processing.
• Experience with computer vision methods applied to scientific or engineering image data (e.g., segmentation, object detection, feature extraction).
• Familiarity with Thermo Fisher Scientific (or FEI) instruments (e.g., Helios platform) or equivalent Tescan, JEOL systems.
• Prior experience in a national laboratory, industrial R&D, or similarly structured research environment.
• Exposure to foundation models or large language models (LLMs) in a research or applied automation context.
• Experience with semantic segmentation frameworks (e.g., Segment Anything Model, U-Net, Mask R-CNN) or related deep learning tools applied to scientific imaging.

Salary Range

• $44,500 - $71,200 (based on full-time 40 hours per week)