🌟 Now Recruiting: AI Project Instructors – Spring 2026 (Paid, $7,000)

Join PAS4AI, an inclusive research and education initiative at Carnegie Mellon University, to instruct autistic community college student teams developing real-world AI projects that advance Responsible AI, collaboration, and accessibility.

As an AI Project Instructor, you’ll guide a small student team in technical development, inclusive teamwork, and reflective AI design, all while integrating your own research interests into hands-on teaching. Instructors receive training in social–emotional learning and inclusive pedagogy, work with a supportive interdisciplinary community, and earn a $7,000 stipend.

🗓️ March 30 – June 5, 2026 | 2 days per week, 1–2:30 PM ET | 9 students total

💡 Ideal for graduate students or postdocs with teaching or instruction experience.

📩 Apply by submitting a 300-word statement on your motivation and teaching experience, a short CV, and optional sample of work or portofilio.

Applications are accepted on a rolling basis until the position is filled.

For more information visit: https://cmu-variability.github.io/pas4aiworkforce/instructor_app/

For questions, please contact Andrew Begel and Ren Butler (abegel@andrew.cmu.edu, ddbutler@andrew.cmu.edu):

Quick Details

Location: Remote / Hybrid (Carnegie Mellon University)

Duration: March 30, 2026 – June 5, 2026 (10 weeks)

Hours per week: 12 hours a week

• 3 hours of synchronous instruction (2 1.5-hour Zoom sessions)
• 2-2.5 hours of 1:1 instructor check-ins with students (1 check-in per student)
• 3 hours of asynchronous student support on Discord
• 3 hours grading technical projects, writing assessments of student social-emotional development, and communication learning
• 1-hour staff meeting

Schedule: 2 days per week synchronous Zoom sessions, 1:00–2:30 PM ET

Compensation: $7,000 per course

About the Course

The Preparing Autistic Students for the AI Workforce (PAS4AI) course aims to design and deliver accessible, team-based learning experiences that prepare autistic community college students for AI-integrated careers. Our interdisciplinary curriculum combines AI fundamentals, Responsible AI practices, and leadership skills through experiential learning. Students work in small, instructor-led project teams to develop real-world AI applications while building communication confidence, technical fluency, and psychological safety in teamwork. In Spring 2026, the course will bring together 9 students for collaborative AI projects co-instructored by graduate and postdoctoral researchers. Each instructor supports one student team, guiding both their technical development and professional growth.

Role Overview

AI Project Instructors are educators, researchers, and/or practitioners who guide undergraduate teams of 3-5 students in applied AI projects. Our research team has created a 10-week curriculum along with instructional guidance and teaching materials for instructors to use to teach the course. Students will complete and remix a series of AI projects that reflect the goals and beliefs about AI development, social relationships, and emotional wellbeing and personal identities. Instructors provide:

• Technical guidance in areas such as Python programming, LLM integration, API-based project development, prompt engineering, model evaluation, and ethical AI analysis.
• Coaching on teamwork, communication, and inclusive collaboration practices.
• Coaching on self-reflection and goal-setting
• Support for integrating Responsible AI and ethical reflection into project decisions.
• Feedback on code, research design, and final presentations.

Instructors are encouraged to bring their own research and professional interests into the course to co-create authentic, mutually beneficial learning experiences.

Benefits for Instructors

• Gain hands-on experience teaching and instructing diverse student teams on real AI projects.
• Build a portfolio of teaching, codesign, and instructoring artifacts relevant to academia and industry.
• Collaborate within an interdisciplinary community of practice focused on Responsible AI, education, and accessibility.
• Contribute to inclusive education and workforce pathways for underrepresented learners in computing.
• Receive structured guidance on teaching, social-emotional learning, mentoring, and inclusive instruction through the PAS4AI instructor orientation.
• Stipend of $7,000 for teaching the course.

Required Qualifications

• Enrollment in or completion of a graduate degree (Master’s or Ph.D.) in Computer Science, Artificial Intelligence, Human–Computer Interaction, Learning Sciences, or a related field.
• Demonstrated experience teaching, instructoring, or facilitating technical learning (e.g., course instruction, coding clubs, lab instructoring, TA roles).
• Strong interpersonal communication and commitment to inclusive, supportive pedagogy.
• Ability to articulate technical concepts clearly and guide student inquiry rather than simply provide answers.

Preferred Qualifications

• Prior teaching experience at the high school, college, or community level, or experience instructing neurodiverse learners.
• Familiarity with Responsible AI, Human-AI Interaction, or Computing Education research.
• Interest in integrating personal or lab research into project-based instruction.
• Awareness of social-emotional learning and the role of psychological safety in team performance.
• Commitment to collaborative teaching and iterative improvement through feedback and reflection.
• Experience interacting with autistic or neurodivergent individuals.

Training and Expectations

Instructors will participate in a two-part orientation and ongoing community meetings designed to prepare them for inclusive, empathetic instruction. Training emphasizes:

• Identifying tacit prerequisite knowledge and preparing to teach foundational concepts as needed.
• Reframing knowledge gaps into opportunities for growth.
• Supporting interdependence and reflective teamwork in AI learning environments.

To Apply

📩 Please submit the following materials to Andrew Begel (abegel@andrew.cmu.edu) and Ren Butler (ddbutler@andrew.cmu.edu) via the application form :

• A short statement (≤300 words) describing your motivation for instructing and how your research or teaching interests align with PAS4AI and SAFER-AI.
• A brief CV or résumé highlighting teaching and/or AI or computing education research experience.
• (Optional) A link to a project, publication, or resource that reflects your teaching or technical work.

Applications will be reviewed on a rolling basis until positions are filled.