- Plan and execute cutting-edge research to advance AI wearable research.
- Collaborate with dynamic teams of engineers, designers, and researchers.
- Organize and lead research activities such as designing and building prototypes, algorithm development, experimental design, data collection, and analysis.
- Write and publish high-quality scientific articles.
- Communicate research activities and findings to collaborators across various disciplines.
- Take big problems and deliver clear, compelling, and creative proposals for how to solve them at scale.
- Produce publishable research in top-tier journals or at leading international conferences.
- Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Robotics, AI/ML, Electrical Engineering, or relevant technical field.
- 3+ years of research experience in SLAM, multimodal sensor fusion, or related fields, as shown in prior publications and portfolio.
- Hands-on experience building robust real-time SLAM systems.
- Programming proficiency in languages such as Python and C++.
- Experience working with data from sensors such as cameras, IMUs, radar, or depth sensors.
- Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow).
- Cross-group collaboration and cross-culture collaboration.
- Clear and concise communication, both written and verbal.
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
- Proven track record of achieving research results and innovation as demonstrated by patents or first-authored peer-reviewed publications in leading conferences or journals such CVPR, ECCV, ICCV, ICRA, IROS, RSS, IRSS, UIST, ISMAR.
- Familiarity with popular framework and libraries. (e.g., ROS, SLAM libraries like ORB-SLAM, VINS-Fusion, RTAB-Map, LSD-SLAM).
- Knowledge of state estimation, probabilistic robotics, and optimization techniques.
- Expertise in multimodal deep learning, including attention-based models or spatiotemporal networks.
- Advanced understanding of calibration techniques and noise modeling for multimodal sensors.
- Experience working and communicating cross functionally in a team environment.
- Intent to return to degree program after the completion of the internship/co-op.
- Availability for minimum 16 consecutive week internship.
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