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Post Doc Opportunity (Personalized balance training) at Univ of Michigan – Ann Arbor
A postdoctoral fellow position is available in the Department of Mechanical Engineering at the University of Michigan to develop and assess a personalized balancing training technology. Age-related declines in balance function drastically impact the quality of life and present long-term care challenges; falls are the leading cause of fatal and non-fatal injuries among older adults. 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 and individuals with sensory dysfunction (e.g., vestibular disorders).
A cover letter is required for consideration for this position and should be attached as the first page of your CV. The cover letter should address your specific interest in the position, outline skills and/or experiences that directly relate to this position, and include complete contact information for at least two professional references. Please submit a single pdf file with the cover letter and CV (optional: you may also submit up to two representative publications as part of the single pdf file). Review of applications will begin immediately.
For applicants with backgrounds in engineering or kinesiology: 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.
Applications must be submitted electronically at: https://careers.umich.edu/job_detail/210206/research-fellow-biomechanics-background
For applicants with a background in physical therapy: The candidate will be expected to work collaboratively with an interdisciplinary team of researchers (including a neurologic certified physical therapist) and students to develop experimental protocols, recruit participants, collect and analyze data, and disseminate findings.
The candidate should have a doctoral degree in physical therapy, prior balance-related clinical experience, prior balance-related research experience, and effective oral and written communication skills.
Applications must be submitted electronically at: https://careers.umich.edu/job_detail/210213/research-fellow-physical-therapy-background
Kathleen Sienko, Ph.D., Department of Mechanical Engineering, University of Michigan; sienko@umich.edu
Wendy Carender, PT, MPT, NCS, Department of Otolaryngology, Michigan Medicine; wcaren@umich.edu
Xun Huan, Ph.D., Department of Mechanical Engineering, University of Michigan; xhuan@umich.edu
Lauro Ojeda, M.S., Department of Mechanical Engineering, University of Michigan; lojeda@umich.edu
Leia Stirling, Ph.D., Department of Industrial and Operations Engineering, University of Michigan; leias@umich.edu
Jenna Wiens, Ph.D., Department of Electrical Engineering and Computer Science, University of Michigan; wiensj@umich.edu
A postdoctoral fellow position is available in the Department of Mechanical Engineering at the University of Michigan to develop and assess a personalized balancing training technology. Age-related declines in balance function drastically impact the quality of life and present long-term care challenges; falls are the leading cause of fatal and non-fatal injuries among older adults. 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 and individuals with sensory dysfunction (e.g., vestibular disorders).
A cover letter is required for consideration for this position and should be attached as the first page of your CV. The cover letter should address your specific interest in the position, outline skills and/or experiences that directly relate to this position, and include complete contact information for at least two professional references. Please submit a single pdf file with the cover letter and CV (optional: you may also submit up to two representative publications as part of the single pdf file). Review of applications will begin immediately.
For applicants with backgrounds in engineering or kinesiology: 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.
Applications must be submitted electronically at: https://careers.umich.edu/job_detail/210206/research-fellow-biomechanics-background
For applicants with a background in physical therapy: The candidate will be expected to work collaboratively with an interdisciplinary team of researchers (including a neurologic certified physical therapist) and students to develop experimental protocols, recruit participants, collect and analyze data, and disseminate findings.
The candidate should have a doctoral degree in physical therapy, prior balance-related clinical experience, prior balance-related research experience, and effective oral and written communication skills.
Applications must be submitted electronically at: https://careers.umich.edu/job_detail/210213/research-fellow-physical-therapy-background
Kathleen Sienko, Ph.D., Department of Mechanical Engineering, University of Michigan; sienko@umich.edu
Wendy Carender, PT, MPT, NCS, Department of Otolaryngology, Michigan Medicine; wcaren@umich.edu
Xun Huan, Ph.D., Department of Mechanical Engineering, University of Michigan; xhuan@umich.edu
Lauro Ojeda, M.S., Department of Mechanical Engineering, University of Michigan; lojeda@umich.edu
Leia Stirling, Ph.D., Department of Industrial and Operations Engineering, University of Michigan; leias@umich.edu
Jenna Wiens, Ph.D., Department of Electrical Engineering and Computer Science, University of Michigan; wiensj@umich.edu