Research Associate II - Robotics Institute

Carnegie Mellon University•Pittsburgh, PA

About The Position

Carnegie Mellon University is seeking a full-time Research Associate II for the Robotics Institute, focused on computer vision and machine learning for human behavior analysis and modeling. The role investigates algorithms and models for understanding human behavior from video, including efficient perceptual algorithms for behavioral cue extraction and methods for modeling interactions between people. The research may use one or multiple cameras and supports applications in medical research and affective computing. Under general supervision, the Research Associate II designs experiments and research protocols and performs complex analysis to report results. The position involves developing artificial intelligence and machine-learning algorithms for video-based human behavior modeling and classification, including deep learning approaches. The associate works with team members to develop and maintain usable, efficient software; designs, develops, tests, and maintains applications or system programs; and contributes to functional specifications and requirements. Research tasks are performed according to established protocols, including collecting, recording, storing, analyzing, and reporting data. The role also includes communicating project progress to the research director, maintaining scientific integrity and accurate data storage, reporting incidents that could affect project goals or workflow, improving methods and protocols, coordinating work, adapting to changing priorities, and collaborating with interdisciplinary partners. The position is located in Pittsburgh, Pennsylvania, and is listed as staff, fixed term, full-time, and hourly. Applicants must be legally authorized to work for CMU in the United States; CMU will not sponsor or assume sponsorship of an employment visa for this opportunity. OSHA Hazardous Materials Safety Training is listed as training for the role.

Requirements

Master of Science (MS) in computer vision, machine learning, artificial intelligence, or a closely related field.
Strong programming skills.
Strong background in machine learning, computer vision, or human behavior modeling, with specialization in one or more of the following: supervised, unsupervised, or self-supervised learning; large vision models; multimodal foundation models; or transfer learning.
Research experience in multimodal human behavior analysis, affective computing, AI for healthcare, and multimodal machine learning.
Very good presentation, communication, and organizational skills.
Must be currently legally authorized to work for CMU in the United States; CMU will not sponsor or take over sponsorship of an employment visa.

Nice To Haves

Publications in top machine-learning and/or computer-vision conferences and journals.
Research experience involving clinical applications, such as depression or pain.
Experience and/or enthusiasm for mentoring students.
Experience analyzing questionnaires and surveys.
Experience with grant proposal preparation and coordination.

Responsibilities

Write code and develop state-of-the-art theoretical and practical AI and machine-learning algorithms for video-based human behavior modeling and classification using deep learning networks.
Work with team members to develop and maintain software for efficiency and usability.
Design, develop, test, and maintain applications or system programs.
Gather and provide input on functional specifications and requirements.
Perform approved research tasks according to defined protocols and procedures, including appropriate data collection, recording, storage, analysis, and reporting.
Follow research policies and procedures and maintain scientific integrity, including accurate data storage.
Communicate daily research progress through meetings and written reports to the research director.
Follow mandatory reporting procedures for incidents or events that affect, or could affect, project goals and workflow.
Optimize protocols and improve existing methods.
Coordinate work to achieve productivity and adapt to changing priorities to maintain a consistent workflow.
Interact with interdisciplinary professional partners.
Perform other duties as assigned.