Title:
Motion Capture Coordinator

Department:
Hillier College of Arch & Design

Reports To:
Assistant Professor, School of Art and Design

Position Type:
Staff

Position Summary:
The Strengthening American Infrastructure (SAI) project seeks to improve the usability of public transportation hubs for all Americans, regardless of ability. Using Virtual Reality (VR) simulations, we are studying how people with varying mobility and perceptual abilities navigate public spaces. This research will inform the design of more efficient and accessible public transportation hubs, expanding opportunities for all. We are in collaboration with the Rutgers University Dept. Of Psychology. Rutgers will be performing the human subject studies. At NJIT, we will be recording motion capture data of people that can be used for game design.

We are seeking a highly motivated and detail-oriented recent graduate to assist with the motion capture component of this research project. You will play a crucial role in supporting the development and implementation of the motion capture data collection process. This position will provide valuable experience in research methodology, data collection, and project management.

Essential Functions:
Recruitment:

• Assist with the recruitment and screening of participants for motion capture sessions.
• Manage participant scheduling and communication.
• Ensure adherence to all ethical guidelines and informed consent procedures.

Motion Capture Sessions:

• Assist with preparing the motion capture studio and equipment.
• Provide guidance and support to participants during motion capture sessions.
• Accurately capture motion data using specialized software and equipment.
• Ensure data quality and integrity throughout the collection process.

Data Management:

• Organize and manage motion capture data, ensuring proper labeling and storage.
• Assist with data preprocessing and basic analysis.

Collaboration:

• Collaborate with the research team on data collection protocols and procedures.
• Contribute to the development and improvement of data collection processes.

Additional Functions:

• Assist with project-related tasks as assigned.
• Participate in team meetings and contribute to project discussions.

Prerequisite Qualifications:

• Bachelor's degree in a relevant field (e.g., Human-Computer Interaction, Psychology, Human Factors, Computer Science).
• Strong interest in human movement, human-computer interaction, and/or accessibility research.
• Excellent communication and interpersonal skills.
• Ability to work effectively independently and as part of a team.
• Strong organizational and time management skills.
• Experience with motion capture technology and software (e.g., Vicon, MotionBuilder) is a plus.
• Familiarity with data analysis software (e.g., MATLAB, Python) is desirable.
• Commitment to ethical research practices.
• At the university's discretion, the education and experience prerequisites may be exempted where the candidate can demonstrate to the satisfaction of the university, an equivalent combination of education and experience specifically preparing the candidate for success in the position.

Salary Information:
In compliance with the NJ Pay Transparency Law, the hourly rate/range for this position is $25.00 (USD). NJIT considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer. This pay range represents base pay only and excludes any additional items such as incentives, bonuses or other items.

FLSA:
Non-Exempt
Part-Time

Special Instructions to Applicants:
Benefits:

• Gain hands-on research experience in a cutting-edge virtual reality lab.
• Contribute to a project with real-world impact on accessibility and public transportation design.
• Develop valuable skills in motion capture technology, data analysis, and project management.
• Work alongside experienced researchers and learn about the field of human-computer interaction.