A postdoctoral fellow position is available to work in the Department of Mechanical Engineering at the University of Michigan on the development and assessment of a personalized balancing training technology. Age-related declines in balance function drastically impact quality of life and present long-term care challenges; falls are the leading cause of fatal and non-fatal injuries among older adults (OAs) ³ 65 yrs. Successful fall prevention programs include balance exercise regimes, designed to recover, retrain, or develop new sensorimotor strategies to facilitate functional mobility. To enable preventative and therapeutic at-home balance training, we aim to develop models for automatically 1) evaluating balance and, 2) delivering personalized training guidance for community dwelling OA. The candidate will be expected to work collaboratively with a team of researchers and students to develop experimental protocols, collect and analyze data, contribute to the development of data-driven models for automatically evaluating balance, and disseminate findings. The candidate should have a doctoral degree in engineering or kinesiology, prior experience collecting and/or analyzing kinematic data (inertial measurement unit and/or passive motion tracking data), an interest in learning and collaborating with researchers in machine learning and data science, and effective oral and written communication skills. A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position. Your resume attachment should also include the names and contact information for three references. Review of applications will begin immediately. Applications must be submitted electronically at:
https://careers.umich.edu/job_detail/182159/research_fellow
