Adjunct Instructor in AI for Human Centered Design

Brandeis University’s Rabb School is seeking an Adjunct Faculty member for RUCD 125: AI for Human Centered Design for the 2027 Spring 1 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in User-Centered Design and Masters Certificate in Technology Futures.

Course Description: Introduces students to the principles, methods, and ethical considerations for applying artificial intelligence within user experience and product design contexts. Emphasizes responsible integration of AI tools to augment, rather than replace, human-centered design processes. Students will explore how to leverage generative AI, machine learning, and automation to enhance research, prototyping, and personalization, while maintaining transparency, inclusivity, and trust in digital experiences.

Core Course Responsibilities Summary

• Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.

• Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.

• Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.

• Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.

Qualifications:

• Required:

  • Master’s degree in Human Factors, HCI, User Experience, or related discipline

  • Current, active employment in Human Factors, HCI, User Experience, or related disciplines

  • 5+ years of professional experience in UX or related disciplines

  • Applied experience designing AI agents and/or AI-enabled software

  • Applied knowledge of AI design and prototyping tools, including Figma Make

  • Applied knowledge of generative AI tool use for user experience research

  • Basic Vibe coding proficiency

  • At least 1 year of teaching or training experience (preferably online/asynchronous)

  • Proficiency with LMS platforms and digital authoring tools

  • Familiarity with analytical tools, collaborative platforms, and interdisciplinary teamwork

  • Strong communication, organization, and independent work skills

• Preferred:

  • Experience teaching or developing graduate-level online courses

  • Prior online teaching experience at the graduate level 

  • Knowledge of global learner personas and culturally responsive pedagogy

  • Familiarity with Moodle LMS and digital authoring tools (e.g., H5P)

Application Process: Interested candidates should submit:

A cover letter highlighting relevant qualifications and teaching experience.

A current CV or resume.

Contact information for three professional references.

Application review begins 9/15/2026 though we will continue to accept submissions on an ongoing basis.

This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.

Compensation for this position is $6573.15

Pay Range Disclosure

The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.

Equal Opportunity Statement

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").