Machine Learning/Computer Vision for 3D Scene Understanding/Reconstruction
Machine Learning/Computer Vision for 3D Scene Understanding/Reconstruction (Job Number: P17INT-22)

This title includes multiple positions which focus on research and development of computer vision, machine learning and optimization algorithms.  The candidate is expected to work on one of the following topics:

  • 3D traffic scene reconstruction from video
  • Joint 2D/3D Data Fusion for Dynamic Traffic Scene Analysis

 

Qualifications:

  • PhD or MS in computer science, electrical engineering, or related field
  • Strong familiarity with computer vision and machine learning techniques pertaining to 3D reconstruction, SLAM, visual recognition, and deep learning
  • Highly proficient in software engineering using C++ and Python

 

Preferred Qualifications:

  • Experience in open-source Deep Learning frameworks such as TensorFlow or Caffe
  • Hands-on experience in developing algorithms for 3D reconstruction, SLAM, and visual recognition
  • Experience in Robot Operating System (ROS)
  • Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents
  • Strong publication record in one or more of the following areas: computer vision, machine learning