3D Vision Research Intern RAL
Location | Sunnyvale, CA |
Remote | See job post for details |
First listed | In the last 6 months |
Job Description
The Robotics and Auto-Driving Lab (RAL) of Baidu Research USA is looking for intern candidates with strong 3D vision background. We aim to build a multi-disciplinary research team that combines expertise in computer vision, robotics, machine learning, human-robot interaction, NLP, graphics, and simulation to study holistic solutions, as we strongly believe that the most significant advancements come from the cross pollination of different areas. We aim to become a bridge that closes the gap between academic research and industrial applications. By establishing and maintaining a close relationship with world leading universities and using Baidu’s well established engineering talent, we strive to be the first to bring research lab results, from either internally or externally, to market.
The selected candidates will focus on conducting core 3D vision research with applications to versatile real world problems.
Key Responsibilities:
- Research, design, implement, and evaluate novel 3D vision and deep learning algorithms and systems for real world problems
- Participate in software prototyping and experimental evaluation
- Contribute to academic publications
Qualifications:
- PhD/MS student in Computer Science, Electrical Engineering, or related field
- Proven track record in conferences/journals
- Experience in at least one of following 3D vision, graphics, or other related areas (human 2D/3D pose estimation and tracking, 3D reconstruction, character animation, autonomous driving, robot perception, and deep learning)
- Good programming skills in Python or C/C++
Culture Fit:
- Mission alignment: If you want to be part of a team to accomplish this great mission, we will provide you the best possible platform to do that.
- Self-directed: We work best with people that are driven, motivated, and aspire to greatness.
- Hungry to learn: We are eager to see you learn new skills and grow.
- Team orientation: We work in small, fast-moving teams. We watch out for each other and go after big goals together as a team.
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