News

A team of faculty at Stanford University, led by Professor Scott Delp, is accepting applications for a Postdoctoral Fellowship in biomechanical engineering and human performance science. Candidates are expected to have a PhD in a related discipline and experience with motion capture technology and biomechanical analysis. Individuals with backgrounds in biomechanics, neuroscience, biomedical informatics, robotics, and computer science are all welcome to apply. The position will be in the Human Performance Lab at Stanford, and is affiliated with the Neuromuscular Biomechanics Lab and the Wu Tsai Human Performance Alliance. 

We are searching for outstanding individuals to join our team and develop new methods to measure, simulate, and analyze human movement. Our approach will leverage novel data sources, such as real-world wearable sensors and video, experimental analysis, biomechanical modeling, and state-of-the-art models of neural control. Funding is available to support fellows for two or more years. Fellows will have the opportunity to build an interdisciplinary scientific network, participate in mentoring graduate and undergraduate students, and present their work at international scientific meetings.

Stanford University is an affirmative action and equal opportunity employer, committed to increasing the diversity of its workforce. We encourage 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.

Candidates must have: 

• A PhD in engineering, computer science, neuroscience, or related fields
• Strong record of publication and excellent communication skills
• Experience in biomechanics experiments and modeling

Experience in one or more of the following areas is also desirable; experience in all of these areas is not required: motion measurement, EMG analysis, biomechanics, exercise physiology, neural control of movement, wearable sensors, musculoskeletal modeling, biomedical imaging, computer vision, reinforcement learning, machine learning, computer animation, physics-based simulation, robotics and controls. The ability to perform biomechanical experiments, analyze complex data, collaborate on a research team, and write high-impact research papers is essential.

Interested applicants should:

(1) Send a letter indicating their interest and experience, a CV, and copies of two representative publications via e-mail to human-performance@stanford.edu.

(2) Complete the short online form.

(3) Arrange for two letters of reference to be sent to human-performance@stanford.edu 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.