The Department of Bioengineering at the University of Washington invites applications for a full-time Assistant Teaching Professor position, emphasizing AI in Bioengineering, including responsible, transparent, and equitable uses of computational tools in biomedical contexts but considering candidates with expertise in a broad range of biomedical engineering fundamentals. We particularly welcome candidates whose work critically engages with the reliability, safety, interpretability, and societal implications of AI in healthcare and biological systems.  Assistant Teaching Professors are non-tenured faculty members and are hired on multi-year appointments with a 9-month service period (September 16 through June 15) and may have additional opportunities to teach during the summer.  The anticipated start date is September 16, 2026.    

The base salary range for this position will be $8,000 to $12,000 per month (with a nine-month service period), commensurate with experience and qualifications, or as mandated by a U.S. Department of Labor prevailing wage determination.  Other compensation may include a one-time relocation incentive (up to $12,000), if applicable. 

UW Bioengineering is jointly administered by the School of Medicine and the College of Engineering, with faculty and students continually reach across traditional boundaries in education and research to drive healthcare forward. As AI increasingly shapes biomedical research and healthcare decision-making, we also value candidates who can help students critically understand how algorithmic systems affect equity, access, bias, and real-world clinical workflows.  The successful candidate will be expected to integrate AI responsibility perspectives into teaching and mentoring, including issues of fairness, transparency, appropriate data use, and community impact.  

This position will demonstrate a broad range of biomedical knowledge and skills in one or more of the following areas: application of AI to biomedical applications, development of AI, machine learning, and data-driven modeling methods, physiology, transport, fluid and solid mechanics, systems analysis, circuit prototyping, technology transfer, and biomedical design practices, in addition to responsible AI practices, such as model interpretability, validation on diverse populations, uncertainty quantification, and trustworthy deployment in biomedical settings. While this position is expected to specialize in AI-related fields, all qualified candidates are welcome to apply.

The successful candidate will teach or co-teach existing courses in the department (for a full list, please see undergraduate, master’s, and Ph.D.), which may include lecture, lab, and capstone design. The appointee is also expected to develop and teach one or more new undergraduate-level and graduate-level course(s) integrating core areas of bioengineering. 

This position will demonstrate a passion for innovative, interdisciplinary teaching and curriculum design, and the ability to engage a diverse student body through project-based learning. This position offers an opportunity to help shape the next generation of bioengineers proficient in both biological systems and computational tools, and to contribute to the department’s broader educational mission at the interface of engineering, medicine, data science, and community health.  This position represents a unique opportunity to help inform national norms for the integration of responsibility and equity AI into biomedical engineering education.

University of Washington faculty engage in teaching, scholarship, and service. While Teaching Professors primarily focus on education and service, they are also expected to contribute to pedagogical and/or engineering scholarship. This scholarship is broadly defined and may include the development of new instructional materials, innovative teaching and mentoring methods, outreach activities, novel student assessment approaches, leadership in professional associations, and the dissemination of their work within the university and beyond. 

Positive factors for consideration include, but are not limited to:

·        Demonstrated excellence in teaching or mentoring, with experience in classroom instruction or design-based learning

·        Experience developing laboratory-based courses and project-based learning modules

·        Knowledge of industry practices, including regulatory oversight and manufacturing processes

·        Integration of engineering computation software in curriculum design

·        Advising students on capstone projects or independent research in biomedical technology

·        Involvement in interdisciplinary collaboration and curriculum innovation, especially in emerging biomedical topics, including integrating principles of safety, accountability, and responsible model evaluation into AI-based biomedical design.

·        Ability to foster connections between students, academia, and industry partners to support learning and professional development

·        Ability to develop and teach in both the use of AI to support biomedical design practice, and the generation of AI methods suitable for biomedical technology, and to play a central role in modernizing our current curricula with AI-based perspectives.