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Research Associate II - Robotics Institute

Carnegie Mellon University

Salary not specified
Aug 22, 2025
Pittsburgh, PA, US
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Investigate new algorithms and models for analyzing and understanding human behavior from video.

Requirements

  • computer vision and machine learning
  • design of efficient perceptual algorithms for behavioral cue extraction
  • novel approaches for the modeling people interaction
  • video classification using deep learning networks

Responsibilities

  • Write code and develop novel theoretical and practical state of the art artificial intelligence/machine learning algorithms that are focused on human behavior modeling related to video classification using deep learning networks for end-users.
  • Work with other team members to develop and maintain software for maximum efficiency and usability.
  • Designs, develops, tests and maintains applications or system programs.
  • Gathers and provides input on functional specifications and requirements
  • Perform approved research project tasks according to defined protocols and procedures including appropriate collection, recording, storage, and analysis of data, and reporting of results.
  • Follow appropriate research policies and procedures and maintains scientific integrity including accurate data storage.
  • Communicate the daily progress of research projects via meetings with, and written reports to the research director.

Other

  • Master or bachelor degree in computer science, applied mathematics, electrical and/or computer engineering with a focus on computer vision/machine learning.
  • Three years’ experience in a research environment with at least one year in the designated specialty of research.
  • Strong interpersonal, verbal, and written communication skills.
  • Strong organization and planning skills, careful attention to detail with strong follow-through, able to prioritize and organize tasks effectively to accomplish objectives in a timely matter.
  • Enthusiastic about collaborating with partners from multiple disciplines and institutions.