Description: This position offers the opportunity to work on a broad and exciting set of problems related to processing of 3D point cloud data, including recognition, registration, segmentation, tracking, representation, and transmission.
- Propose, create, and implement state-of-art point cloud segmentation and classification algorithms.
- Develop algorithms for spatial and temporal registration of 3D point cloud data, recorded from multiple LiDAR sensors.
- Develop and evaluate metrics to verify the reliability of the proposed algorithms.
- Participate in ideation, creation, and evaluation of various related technologies, including 3D SLAM.
- Contribute to a portfolio of patents, academic publications, and prototypes to demonstrate research value.
- Participate in software development and implementation on various experimental platforms.
- PhD in computer science, electrical engineering, or related field.
- Strong familiarity and research experience in 3D computer vision and machine learning.
- Hands-on experience in one or more of the following: LIDAR data processing, Simultaneous Localization and Mapping (SLAM), Perception, Machine Learning, Sensor Fusion.
- Preferred hands on experience in handling multi-modal sensor data.
- Highly proficient in software engineering using C++ and Python.
- Preferred experience with Point Cloud Library (PCL), Robot Operating System (ROS), and GPU programming.
- Preferred experience in open-source Deep Learning frameworks such as TensorFlow or Caffe.
- Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents.
- Strong publication record one or more of the following areas: 3D computer vision, machine learning, or SLAM.
Application Instructions: Please send an email to firstname.lastname@example.org with the following:
- Subject line including the job number you are applying for
- Recent CV
- A cover letter explaining how your background matches the qualifications
Candidates must have the legal right to work in the U.S.A.