Post Doctoral Fellow

Key Skills

Computer Vision (CV), Effective communication skills, Machine learning techniques, Neuroscience, Planning and organization

Job Description

The Sports Performance And Research Center (SPARC) at Flowery Branch is seeking a candidate to fill a postdoctoral research fellow position in the area of biomechanics and neuroscience of injury prevention and sports performance enhancement. SPARC is a state of the art biomechanics and neuroscience lab, and offers unique opportunities to develop engineering solutions for rapid proliferation of technology and scientific research. As a critical component of this research, the candidate will work to develop novel markerless motion capture techniques, with direct applications in virtual reality sports simulation, biomechanical assessments, rehabilitation, and neuroimaging. During the course of their fellowship, the candidate can expect to further develop their technical expertise and scientific skills, and will be encouraged to disseminate their work to the broader scientific community. Candidates should be comfortable leading their own project, but also working as part of a larger research team. The position is a temporary appointment that will renew yearly depending on satisfactory performance and available funding. Appointments may not exceed 5 years. 

Minimum Qualifications:

A doctoral degree or equivalent in an appropriate field. Strong scientific writing ability and excellent communication skills. The ability to work effectively with colleagues on complex multi- disciplinary problems. Additional qualifications as specified by the Principal Investigator.

Preferred Experience:

Expertise in machine learning and computer vision are strongly preferred, along with a thorough understanding of human pose estimation. Additionally, experience with biomechanics and/or neuroscientific applications are recommended. A firm understanding of good software development practice and organizational skills are encouraged. The candidate must be comfortable working with a variety of computing hardware with peripheral devices such as cameras, force plates, treadmills, and electrophysiological measurement systems (EEG/EMG).

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