Nus
Part-time Faculty, Master of Arts in Sport and Performance Psychology/ MATE Supervisor
Remote, USA · Internship
Sponsorship not specifiedDetected 14 days ago
About the role
- We invite you to join our Part-time Faculty in the Master of Arts in Sport and Performance Psychology program.
- We are searching for instructors who can supervise student interns during this 18-week Mentored Applied Training Experience course.
- The successful candidate will have a demonstrated record of or potential for excellence in teaching in their field and a commitment to serving the university's diverse adult student body.
Responsibilities
- Lead classroom sessions on-site and/or online according to university policies.
Requirements
- Master's degree in Sport Psychology, Kinesiology, or a Sport Science-related field
- At least 2 years' experience in the field of performance enhancement training.
- If selected, candidates with international degrees may be required to submit translation/degree evaluation from one of our approved agencies
- To teach in our program, you must have an advanced degree in Sport Psychology, Kinesiology, or a Sport Science-related field.
- Possess the Certified Mental Performance Consultant (CMPC) certification through the Association for Applied Sport Psychology and/or be an approved mentor on the Association for Applied Sport Psychology (AASP) registry.
- Must reside and be eligible to work in the United States.
- Resume / Curriculum Vitae
- Unofficial Transcripts
Nice to have
- Cover Letter highly preferred
Compensation
- Hourly: $26.63 - $28.89
- Today, we educate a diverse student body from across the U.S. and around the globe, with more than 230,000 alumni worldwide.
Benefits
- Emphasize student-centered learning by promoting student inquiries and encouraging participation in their own learning.
- Maintain a positive, safe, student-centric learning environment
- Since 1971, our mission has been to provide accessible higher education to adult learners.
This listing is sourced directly from Nus's careers page and normalized into a canonical job model.