Faculty & Staff Recruitment

Thomas Jefferson University invites applications for full-time faculty positions at the Assistant or Associate level in Health Artificial Intelligence to support the Master of Science in Health Artificial Intelligence (MS-HAI) program. We seek interdisciplinary scholars and practitioners who can teach graduate-level courses, mentor students, and lead or contribute to scholarly and applied work at the intersection of artificial intelligence and healthcare.

The faculty member will play a central role in delivering an innovative curriculum, mentoring students on real-world healthcare AI projects, engaging in interdisciplinary research and innovation activities, and contributing to collaborations across Thomas Jefferson University, Jefferson Health, industry partners, and community stakeholders. The position is full-time and based on the Center City campus in Philadelphia, Pennsylvania.  The ideal candidate will be an excellent teacher experienced in online education, a collaborative colleague, student-centered in their approach, and committed to advancing the responsible use of artificial intelligence to improve healthcare delivery, outcomes, and population health.

The Assistant/Associate Professor will work with faculty colleagues, College leadership, staff, students, alumni, and health system partners to strengthen the MS-HAI program through excellence in teaching, scholarship, innovation, and service.

Teaching & Curriculum Development
Student Mentorship & Advising
Scholarship, Research, and Innovation
Health System & Industry Engagement
Service and Program Leadership 

Education Required:
Terminal degree in a relevant field (PhD, DrPH, MD, DO, or equivalent.)

Demonstrated expertise in one or more of the following areas:
Artificial Intelligence
Machine Learning
Healthcare Analytics
Biomedical Informatics
Clinical Informatics

Experience teaching or training students and/or professionals in online environments. Strong communication skills and the ability to engage both technical and clinical audiences. Commitment to student success, mentorship, and interdisciplinary collaboration.

Preferred Qualifications:
Experience applying AI, machine learning, or data science in healthcare settings.
Familiarity with healthcare data systems and standards, including EHRs, FHIR, and HL7.
Record of publications, funded research, or applied innovation commensurate with rank.
Experience collaborating across academic, healthcare, and industry environments.
Industry, consulting, or health system leadership experience related to AI or digital health.

Interested candidates should submit an on-line application with current CV, cover letter, statement of teaching philosophy, and a research statement. Enter in search box Job ID # REQ: 0037737

Cover letter can be addressed to the Search Committee Chair: Richard W. Hass, PhD.