If you are a current Barnard College employee, please use the internal career site to apply for this position.

Job:

Job Description:

The Design Center at Barnard College is investigating whether university makerspaces can build their own custom software for novel fabrication methods using AI, unique to their specific teaching and learning environment, without relying on specialized computer science or coding expertise. The current focus is a G-code–generating application that makes a CNC machine intuitive for beginners to use, with the approach expected to extend to additional fabrication tools such as clay 3D printers. Importantly, AI is not being used to generate G-code on demand. Instead, AI is used to build a free-standing, reusable tool that helps students learn how to operate fabrication technologies and produce the files needed to execute their own projects. This work sits within the broader umbrella of pedagogy research and is intended for submission to an academic conference.

Under the leadership of Design Center Faculty Director Karen Fairbanks and Associate Director Zoe Ross, the Graduate Research Assistant will support this research by systematically testing software settings, troubleshooting the fabrication workflow, and ultimately helping to conduct user studies and co-author a research paper. The software development itself will continue to be led by Zoe Ross; the Research Assistant’s role centers on testing, documentation, study design and execution, and writing.

Responsibilities include:

·       Systematically test the software’s settings and features across materials and use cases, documenting results in a clear, reproducible way.

·       Troubleshoot the end-to-end fabrication workflow — from file generation through machine operation — and report issues, edge cases, and suggested improvements.

·       Operate the CNC machine (and other fabrication tools) to validate that generated files execute correctly and safely.

·       Help design and conduct user studies with student participants, including preparing protocols, running sessions, and collecting and organizing data.

·       Analyze qualitative and quantitative study data and help translate findings into insights about beginner-friendly, AI-built fabrication software.

·       Contribute to writing and revising a research paper for conference submission.

·       Maintain organized records, notes, and documentation throughout the project.

·       Present progress and findings in weekly meetings.

·       Additional responsibilities as needed.

Skills, Qualifications & Requirements:

·       Demonstrated ability to work on a team in a collaborative environment.

·       Demonstrated ability to work on multiple projects simultaneously.

·       Excellent interpersonal, written, and oral communication skills.

·       Strong organizational skills and attention to detail, with a methodical approach to testing and documentation.

·       Curiosity about fabrication technology and comfort learning new tools and workflows independently.

·       Ability to work independently, follow through on tasks, and communicate progress and blockers proactively.

Required Qualification Summary

·       Current graduate student at Columbia University.

·       Prior research experience.

·       Some fabrication or making experience.

·       Availability of 10 hours per week across the fall and spring semesters (15 weeks each), including attendance at weekly meetings.

Preferred Qualification Summary

·       CNC and/or 3D printing experience.

·       Higher education and/or teaching experience.

·       Research paper writing experience, ideally toward conference or journal submission.

·       Interest in pedagogy, makerspaces, or human-centered/educational technology research.

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the College's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Company:

Time Type: