
location_onLogan Street, Downtown, Pittsburgh, Allegheny County, Pennsylvania, 15262, United States
Carnegie Mellon University's Robotics Institute is a hub for innovation, inspiring changes in the world through cutting-edge research. The institute seeks creative and upbeat individuals who thrive in interesting and challenging work environments to join their team.
The Research Associate I is a pivotal role designed to assist in the development and execution of research projects. This position focuses on the full lifecycle of research, from experiment design and data collection to the analysis of results and technical reporting. The role specifically involves researching SLAM (Simultaneous Localization and Mapping) systems and building or validating quantitative models. Success in this position requires strong problem-solving skills to identify obstacles and develop strategies for progress, as well as the ability to program software in support of job functions when necessary.
Joining the Carnegie Mellon team offers more than just a job; it is an opportunity for professional growth and personal aspiration. The university values the whole package when extending offers, evaluating candidates based on their unique skills, perspectives, and the knowledge gained through education and training. The institution is dedicated to finding the perfect fit for every employee.
Interested candidates are encouraged to apply today to explore this exciting opportunity. For more information on the culture and mission of the institution, please visit the "Why Carnegie Mellon" page.
Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran. The university is committed to diversity and inclusion, ensuring a supportive environment for all employees.
Work model: On-site
Logan Street, Downtown, Pittsburgh, Allegheny County, Pennsylvania, 15262, United States
Pittsburgh, Pennsylvania
Skills: Osl Hazardous Materials Safety Training, Slam Systems, Data Collection, Data Analysis, Research Methodology, Quantitative Models, Statistical Information.
Education: Bachelor's Degree (or equivalent experience may be considered).
Full-Time