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Research Scientist Intern, Machine Perception for Input and Interaction (PhD)Meta Platforms, Inc. • Seattle, Washington, United States
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Research Scientist Intern, Machine Perception for Input and Interaction (PhD)

Meta Platforms, Inc.
  • US
    Seattle, Washington, United States
  • US
    Seattle, Washington, United States
Apply Now

About

Reality Labs (RL) teams are looking for exceptional interns to help us create next generation interaction technologies for virtual and augmented reality. Join a full-stack team working on computer vision, machine learning, geometric and appearance modeling, physically-based modeling, sensor design and fusion, and human computer interaction. We are accepting applications from those interested in (but not limited to) the following areas: *Tracking of hands, bodies and objects and their interactions through machine learning, computer vision and sensor fusion *Egocentric human action recognition and emotion recognition *Hand motion sequence modeling for hand-object interaction using deep generative models or physical simulation *Representation modeling (e.g., implicit, appearance, geometry) of hands, bodies and objects for fast simulation and tracking *Efficient deep learning (e.g., neural architecture search, sparsity, quantized networks) *Interaction design for hands, bodies and objects in virtual reality and augmented reality *Sensor fusion (e.g. of pressure, RF, EXG, IMU) with optical tracking *Efficient and generalizable detectors for predicting keypoints, segmentations, normals, and depth *Accurate and efficient 3D representations of deformable shapes such as clothing and hair
Minimum Qualifications
* Currently has, or is in the process of obtaining, a PhD degree in EE/CS, Applied Math or a related STEM field
* Experience in one or more of the following: computer vision (e.g. tracking, pose estimation, action/emotion recognition), computer graphics (e.g. appearance, geometry, physically-based modeling), robotics (state estimation, optimal control), machine learning (e.g. efficient deep learning, domain adaptation,
  • Seattle, Washington, United States

Languages

  • English
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