Interested candidates should submit the following documents:

1. A cover letter detailing your research experience and how it aligns with both the 3D fabrication and data analytics aspects of this role.
2. A current Curriculum Vitae (CV).
3. Contact information for three professional references.
4. A portfolio or examples of previous 3D design/printing work.

Research Fellow -  Hearing Technology, 3D Fabrication & Auditory Analytics  

The Department of Otolaryngology is seeking a highly motivated and multidisciplinary Research Fellow to join our team researching advanced solutions for the hearing impaired. This unique role bridges physical medical device fabrication and healthcare data informatics.

The successful candidate will lead a project focused on the digital workflow for custom auditory prosthetics, specifically, taking digital impressions of the human ear canal, utilizing CAD software to design custom earmolds, and 3D printing these devices for clinical use. Additionally, the Fellow will be responsible for developing advanced analytics and predictive models utilizing a comprehensive clinical dataset of cochlear implant (CI) patients to improve patient outcomes and mapping strategies.

Custom Earmold Design & Fabrication:

• Perform digital scanning and acquire accurate 3D digital impressions of the ear canals of hearing-impaired patients.
• Utilize Computer-Aided Design (CAD) software (e.g., Fusion 360, Meshmixer, or specialized audiology software) to design anatomically precise, custom earmolds.
• Operate and maintain medical-grade 3D printers (e.g., SLA, DLP) and handle the selection of biocompatible materials.
• Manage the post-processing workflow (washing, curing, polishing) and perform quality assurance to ensure optimal acoustic seal, patient comfort, and safety.

Cochlear Implant Data Analytics:

• Clean, structure, and manage a large-scale clinical dataset comprising audiometric, surgical, and demographic data from cochlear implant recipients.
• Develop statistical and machine learning models (using Python or R) to identify trends, predict patient outcomes, and optimize device programming/mapping.
• Correlate clinical outcome measures with device programming parameters to generate actionable insights for audiologists and surgeons.

Academic & Research Duties:

• Design rigorous experimental protocols and maintain compliance with Institutional Review Board (IRB) standards for human subjects research.
• Prepare and publish manuscripts in high-impact peer-reviewed journals.
• Present research findings at national and international conferences (e.g., ARO, CI, AAA).
• Collaborate closely with a multidisciplinary team of audiologists, otolaryngologists, engineers, and clinical coordinators.
• Assist in mentoring graduate and undergraduate students in the laboratory.

• Ph.D. in Manufacturing Engineering, Mechanical Engineering, Hearing Science/Audiology, or a closely related field.
• Demonstrated experience with 3D scanning, CAD modeling, and 3D printing technologies.
• Strong proficiency in programming languages used for data analysis and machine learning (e.g., Python or R).
• Experience in handling, processing, and analyzing large datasets.
• Excellent written and verbal communication skills, evidenced by a strong track record of peer-reviewed publications.

• Prior experience working with anatomical modeling, agentic AI, Physics informed AI specifically related to design and manufacturing.
• Experience with clinical research, working with patient data, or knowledge of HIPAA and IRB regulations.
• Experience with biocompatible 3D printing resins and ISO standards for medical devices.

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings.  Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.

Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled any time after the minimum posting period has ended.

The University of Michigan is an equal employment opportunity employer.