Undergraduate/graduate intern - software and data infrastructure for autonomous thin film experimentation (Year-Round)

About the role

NLR’s Materials Design and Discovery group is seeking an undergraduate or graduate intern to support the development of digital infrastructure for autonomous semiconductor processing and characterization systems.

Responsibilities

• Develop and maintain Python software for scientific instrument control and laboratory automation.
• Implement APIs, communication interfaces, and messaging systems connecting distributed experimental instruments and control computers.
• Support real-time data exchange, data management, and provenance infrastructure for autonomous experimentation workflows.
• Aid in integration, testing, debugging, deployment, and documentation of software systems.
• Develop tools for monitoring, logging, and visualization of experimental data and system status.
• Collaborate with multidisciplinary teams working in semiconductor processing, materials science, robotics, and artificial intelligence.

Requirements

• 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.
• 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.
• Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution.

Qualifications

• Experience programming in Python.
• Familiarity with software development practices, including version control (e.g., Git).
• Strong analytical and problem-solving skills.
• Ability to work independently and as part of a multidisciplinary research team.
• Strong written and verbal communication skills.
• Ability to quickly learn new technologies and experimental systems.

Preferred Qualifications

• Experience developing software for hardware interfacing, automation, laboratory systems, or scientific instrumentation.
• Experience with communication standards, protocols, and messaging technologies used for instrument integration and distributed systems (e.g., OPC UA, Modbus, MQTT, TCP/IP, SCPI).
• Experience with databases, data pipelines, or data management systems.
• Experience with machine learning, optimization, computer vision, or autonomous experimentation systems.
• Previous experience working with scientific instrumentation, laboratory automation, or experimental research environments.
• Interest in autonomous systems, scientific computing, robotics, or laboratory automation.