The Department of Mechanical Engineering and Materials Science in the Pratt School of Engineering at Duke University invites applicants for a tenure-track faculty position at the Assistant Professor level with research interests at the intersection of artificial intelligence (AI), health, and engineering.  The department seeks candidates that have a strong track record in multiple areas of AI, including supervised and unsupervised machine learning, computer vision, non-linear optimization, decision and reasoning, human-machine interfaces, computationally efficient AI systems at the hardware or software levels, and deployment of AI in resource-limited settings. There is a preference for hires who can successfully interact with the Engineering and Medical schools by leveraging their AI toolkit to advance health applications in medical imaging, embedded sensing, medical implants, enhanced surgical tools and other medical robotic devices, point of care medical diagnostics and therapeutics, decision optimization, screening platforms, materials and structural design, healthcare data science, and large-scale computing.  Applicants are expected to have a doctoral degree and a strong background in any combination of engineering disciplines, ideally with a focus at the intersection of mechanical engineering, materials science, data sciences, scientific computing, and related areas. Joint appointments with the medical school and/or other departments within and outside the school of engineering are possible.  Successful candidates are expected to have an established and innovative research record, be capable of obtaining competitive external research funding, and be committed to teaching and mentoring at both the undergraduate and graduate levels. We seek faculty members committed to building a diverse and inclusive community that fosters excellence in research and teaching.

Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual’s age, color, disability, genetic information, gender, gender identity, national origin, race, religion, sexual orientation, or veteran status.