Research Intern, Pose Estimation

(Pittsburgh, PA)

Careers at Oculus

Part of Facebook

Oculus Research Pittsburgh is looking for exceptional interns to help us make social interactions in VR a reality. Expertise in computer vision, deep learning, and inverse kinematics are especially appreciated, but smart, motivated people with strong coding or hardware backgrounds are more than welcome, and strong math skills are a huge plus. We want to build a broad virtual reality research community, so we encourage publishing. Come join us as we make VR happen!

We are accepting applications from students interested in (but not limited to) the following areas: -Computer vision-Deep Learning-Computer Graphics -All things faces: Detection, Tracking, Animation, and Rendering-All things bodies: Pose estimation, Performance Capture, Action Recognition, Animation, and Rendering-Multimodal Learning-3D Reconstruction

Our internships are sixteen (16) to twenty four (24) weeks long and we have various start dates throughout the year. year.

Responsibilities

  • Experiment with several different types of cameras and lenses.
  • Calibrate capture systems composed of multiple cameras
  • Design ground truth data collection systems.
  • Design simulations for the generation of synthetic data sets.
  • Define and train novel deep models for body 3D pose estimation.

Minimum Qualifications

  • Pursuing a PhD or Masters in Computer Science or related STEM field
  • Must be currently enrolled in a full time degree program and returning to the program after the completion of the internship
  • Excellent interpersonal skills, cross-group and cross-culture collaboration
  • High levels of creativity and quick problem solving capabilities
  • Proven track record of achieving significant results
  • Ability to obtain work authorization in the United States in 2017

Preferred Qualifications

  • Demonstrated software engineer experience via an internship, work experience, coding competitions
  • Experience with computer vision and deep learning and/or inverse kinematics

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