This recruitment is for a two (2) year fixed-term, benefits-eligible position which begins on the start date and may be renewable in the future based on programmatic need and funding availability. All final candidates must successfully complete a background check.

The Wu Tsai Human Performance Alliance at Stanford is a university-wide research initiative that leverages Stanford’s exceptional research, outstanding athletics, and innovative spirit. We are creating a community that draws on diverse efforts across campus to uncover the fundamental principles of peak performance. Through our programs, we are developing the knowledge, the people, and the tools to make optimal health more accessible to all. We hope you will join us in our mission.

As part of the Alliance, we have established a new position in our Human Performance Laboratory, which is directed by Professor Scott Delp. The research engineer will work with a talented team of faculty, staff, postdoctoral fellows, and graduate students to advance our understanding of human movement through state-of-the-art experiments and biomechanical simulation. Creating and sharing software and datasets to advance human performance research is also vital to our mission, and advancing these efforts will be another key part of this role.

More information about the Alliance programs at Stanford is available at:

https://nmbl.stanford.edu

https://humanperformance.stanford.edu

https://humanperformance.stanford.edu/programs/#human-performance-lab

The expected pay range for this position is $95,000 to $117,000 per annum.

Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years since their applicable education, field or discipline; departmental budget availability; internal equity; among other factors.

• Conduct world class research in the Human Performance Lab on projects related to the Human Performance Alliance research priorities, such as revealing the mechanisms of peak performance, preventing sports-related injuries, accelerating rehabilitation from injuries, and building engineering tools and data sets that advance the field.
• Collaborate with researchers on the Digital Athlete Moonshot. Areas of research include:
  • Analyzing large-scale, real-world datasets to uncover new approaches to predict performance and injury risk and customize training;
  • Combining machine learning and physics-based modeling to simulate and analyze movement; and/or
  • Developing novel approaches to study performance with mobile sensors (e.g., video, wearables).  
• Provide support and build community for the Human Performance Lab, in collaboration with the other members of the lab. Roles include:
  • Developing training materials for others working in the lab;
  • Supporting experimental and simulation projects for other researchers in the lab.

• Ph.D. in Bioengineering, Mechanical Engineering, Computer Science, Kinesiology or related field, including research experience in experimental analysis of human movement and a strong record of scientific publications.
• Experience with motion capture, wearable sensors, metabolic measurements, strength assessment, data acquisition, EMG recordings, programming in Matlab and/or Python
• Excellent communication skills and analytical skills.
• Strong organizational skills and ability to collaborate with physicians, scientists, coaches, students, fellows, and rehabilitation professionals
• Ability to lead and manage research projects with a high degree of independence.

• Research experience in data science and machine learning; wearable sensing; and/or biomechanical modeling.
• Familiarity with policies, ethics, and best practices related to data sharing.
• Familiarity with software development best practices.

• Frequently stand/walk, sit, grasp lightly/fine manipulation, and use a telephone, writing by hand.
• Occasionally reach/work above shoulders, grasp forcefully, and sort/file paperwork or parts, lift/carry/push/pull objects that weigh up to 10 pounds.

• Occasional work on evenings and weekends.
• A remote worker arrangement may be considered for candidates with the appropriate background and experience. Remote workers’ schedules are based in the Pacific Time zone.

• Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
• Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
• Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University’s Administrative Guide, http://adminguide.stanford.edu .

The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.

Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.