The Mobilize Center at Stanford University, a newly established National Institutes of Health (NIH) Biomedical Technology Resource Center (BTRC), has an opening for a Distinguished Postdoctoral Fellow with expertise in machine learning for biomedical applications. The Postdoctoral Fellow would be part of the Hazy Research group, led by Christopher Re in Computer Science, and co-advised by Scott Delp in Bioengineering.
The proliferation of devices monitoring human activity, including mobile phones, an ever-growing array of wearable sensors, and video cameras, is generating unprecedented quantities of data describing human movement, behaviors, and health. Mobility and medical imaging data is also being collected daily by hundreds of clinical centers and research laboratories around the world. Gaining insight from these massive and complex datasets will require novel algorithms for large-scale data processing and machine learning.
The Mobilize Center is bringing together leading data science and biomedical researchers to integrate and understand these data using innovative data science techniques, combined with state-of-the-art biomechanical modeling. Current driving biomedical problems include personalized gait retraining for individuals with osteoarthritis; wearable sensor-based metrics for studying children with cerebral palsy and designing exoskeletons; and predictions from neural recordings and wearable sensors in individuals with Parkinson’s disease.
We are searching for an outstanding creative individual to develop and apply the next generation of machine-learned systems to study human mobility and health. The ideal candidate will have strong research skills in data science and machine learning for biomedical applications. Prior experience with machine learning, weak supervision, optimization, wearable sensors, computer vision, software development, and medical informatics is desirable.
Interested applicants should:
(1) Send a letter indicating their interest and experience, a CV, and copies of two representative publications via e-mail to email@example.com.
(2) Complete the short online form.
(3) Arrange for two letters of reference to be sent to firstname.lastname@example.org within two weeks of submitting (1) and (2).
We encourage applicants to also send links to software or simulations that they have developed. The review of applications will begin immediately and continue until the position is filled.
Stanford University is an affirmative action and equal opportunity employer, committed to increasing the diversity of its workforce. It welcomes applications from women, members of minority groups, veterans, persons with disabilities, and others who would bring additional dimensions to the university’s research and teaching mission.