CV0221: Internship - Robust Estimation for Computer Vision
About The Position
MERL seeks a motivated graduate student to conduct research in robust estimation for computer vision. Depending on the candidate's background and interests, the internship may involve topics such as — but not limited to — camera pose estimation, 3D registration, camera calibration, pose-graph optimization, or transformation averaging. The ideal applicant is a PhD student with strong expertise in 3D computer vision, RANSAC, or graduated non-convexity algorithms, along with solid programming skills in C/C++ and/or Python. Candidates should have at least one publication in a leading computer vision, machine learning, or robotics venue (e.g., CVPR, ECCV, ICCV, NeurIPS, ICRA, or IROS). The intern will work closely with MERL researchers to develop and implement new algorithms for visual SLAM (V-SLAM), perform experiments, and document results. The goal is to produce work suitable for submission to a top-tier conference. The start date and duration of the internship are flexible. The pay range for this internship position will be 6-8K per month.
Requirements
- Demonstrated experience in 3D computer vision, RANSAC, or graduated non-convexity algorithms for vision applications.
- PhD student
- strong expertise in 3D computer vision, RANSAC, or graduated non-convexity algorithms
- solid programming skills in C/C++ and/or Python
- at least one publication in a leading computer vision, machine learning, or robotics venue (e.g., CVPR, ECCV, ICCV, NeurIPS, ICRA, or IROS)
Responsibilities
- develop and implement new algorithms for visual SLAM (V-SLAM)
- perform experiments
- document results
- produce work suitable for submission to a top-tier conference
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What This Job Offers
Career Level
Intern
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees
