Biomedical Engineering Assistant Professor — Hybrid/Research

The University of Rhode Island; Kingston (RI); Hybride; USD 100 000 - 140 000; Plein temps

Résumé du poste

The University of Rhode Island invites applications for a tenure-track Assistant Professor in Biomedical Engineering. The successful candidate will develop and teach undergraduate and graduate courses and establish a high-quality research program with collaboration across engineering and health sciences.

We seek researchers working on innovative technologies and computational approaches to health, with interests in biomechanics, biosensors, AI, imaging, and neuroengineering.

Qualifications

• An earned doctorate in Biomedical Engineering or a closely related field at the time of appointment.
• Demonstrated record of scholarly achievement in biomedical engineering, as evidenced by publications, presentations, or projects.
• Demonstrated ability to teach undergraduate courses in biomedical engineering.
• Demonstrated experience working with diverse groups, including, but not limited to, diversity in race, ethnicity, and gender.
• Demonstrated potential to attract external research funding.
• Demonstrated potential to conduct research as part of multidisciplinary teams.
• Demonstrated ability to teach undergraduate and graduate courses in biomedical engineering.

Responsabilités

• Develop and teach undergraduate and graduate courses while establishing a high-quality research program.
• Collaborate with faculty across engineering and health sciences and participate in interdisciplinary initiatives.

Formation

Ph.D. in Biomedical Engineering or closely related field

Description du poste

The University of Rhode Island invites applications for a tenure-track Assistant Professor in Biomedical Engineering. The successful candidate will develop and teach undergraduate and graduate courses and establish a high-quality research program with collaboration across engineering and health sciences.

We seek researchers working on innovative technologies and computational approaches to health, with interests in biomechanics, biosensors, AI, imaging, and neuroengineering.