Course Director of AI Passport Platform and Lecturer - AI Health Initiative (AIHI)

About the role

The AI for Health Institute at the University of Florida seeks a Course Director and Lecturer to lead the AI Passport platform, a multi-audience, governance-literacy-oriented AI education platform.

Responsibilities

• Own the integrity of the AI Passport content backbone across passport instantiations and ensure that SPACER-grounded pedagogy (See, Practice, Share, Reflect) is implemented with fidelity in every module.
• Coordinate module-faculty contributors and hold the line on experiential-learning standards.
• Oversee cohort lifecycle from recruitment through credentialing and partner with the Program Manager on enrollment, onboarding, gating, and learner support.
• Address learner-surfaced tensions (specialty alignment, feedback, navigation, workload) as ongoing curriculum-design problems, not one-time tickets.
• Institute and maintain a fidelity-of-implementation check for each module — whether modules are being experienced as designed, where friction surfaces, and how the curriculum responds.
• Document findings as ongoing scholarly evidence.
• Own the measurement spine of the platform, which includes pre/post microskill assessments, module-level outcomes, governance-literacy credentialing criteria, and the integration of the Meridian front-door assessment into learner routing and personalization.
• Career development: Supervise and develop instructional design, academic specialist, and coach/mentor staff. Build the talent pipeline that the platform requires at scale.
• Coordinate across passport instantiations (Healthcare Workforce, Biomedical Researchers, BioNexus, future passports) to ensure that the shared backbone stays shared, and that audience-specific adaptations are additive rather than divergent.
• Represent the platform in internal UF/UFHealth conversations, at partner institutions, at AIBHS design-studio events, and at national meetings as assigned by the Contact PI.

Qualifications

• Highest degree possible in field or equivalent professional experience; Evidence of pertinent experience for the position and qualifies for the academic unit.
• The ideal candidate will possess:
• One to three years of progressive responsibility in health professions education, curriculum development, or implementation of structured learning programs at the postgraduate or continuing-education level.
• Demonstrated experience designing or leading experiential, case-based, or practice-based learning — familiarity with Kolb's experiential learning theory or equivalent frameworks is expected.
• Demonstrated scholarly productivity appropriate to the rank: peer-reviewed publications, curriculum evaluations, or instrument development.
• Familiarity with AI fundamentals in the health context — not technical expertise, but interpretive competence sufficient to lead faculty discussions on AI governance, accountability, and trust calibration.
• Demonstrated ability to coordinate across multiple stakeholders with divergent priorities and to keep complex programs aligned under ambiguity.
• Experience with competency-based or microskill-based curricular design.
• Experience working in or alongside a research education grant (NIH R25, K12, T32, or equivalent).
• Prior experience leading mixed-methods program evaluation.
• Experience with digital learning platforms (Canvas or equivalent), assessment instruments, and credentialing frameworks.
• Prior scholarly contribution to the adult-learning-science literature, especially in AI education, medical education, or digital learning.
• Experience bridging academia, health systems, industry, or policy communities.

Preferred

• The ideal candidate will possess:
• One to three years of progressive responsibility in health professions education, curriculum development, or implementation of structured learning programs at the postgraduate or continuing-education level.
• Demonstrated experience designing or leading experiential, case-based, or practice-based learning — familiarity with Kolb's experiential learning theory or equivalent frameworks is expected.
• Demonstrated scholarly productivity appropriate to the rank: peer-reviewed publications, curriculum evaluations, or instrument development.
• Familiarity with AI fundamentals in the health context — not technical expertise, but interpretive competence sufficient to lead faculty discussions on AI governance, accountability, and trust calibration.
• Demonstrated ability to coordinate across multiple stakeholders with divergent priorities and to keep complex programs aligned under ambiguity.
• Experience with competency-based or microskill-based curricular design.
• Experience working in or alongside a research education grant (NIH R25, K12, T32, or equivalent).
• Prior experience leading mixed-methods program evaluation.
• Experience with digital learning platforms (Canvas or equivalent), assessment instruments, and credentialing frameworks.
• Prior scholarly contribution to the adult-learning-science literature, especially in AI education, medical education, or digital learning.
• Experience bridging academia, health systems, industry, or policy communities.

Special Instructions to Applicants

Interested candidates should submit: A cover letter describing fit for the position and the rank sought, Current CVA one-page statement on teaching and curriculum philosophy, with specific reference to experiential learning and AI-in-health context, Names and contact information for three professional references.

Health Assessment Required

No