Research Scientist Intern, SLAM and Multimodal Sensing (PhD)
Meta

At Meta Reality Labs Research, our world-class team of researchers, developers, and designers collaborate to create innovative user experiences with contextual AI. As a Research Intern, you will investigate how people and AI agents interact through various interfaces and develop groundbreaking sensing technologies, interactions, and interfaces for wearable devices. Our mission is to invent user interface technologies that drive the next generation of augmented-reality experiences, unleashing human potential by removing barriers between intent and action.In this role, you will combine modalities such as visual, inertial, radar, or depth sensors to enhance localization and mapping in diverse and challenging environments. You will explore cutting-edge techniques, including deep learning, sensor fusion, and novel algorithmic approaches to push the boundaries of SLAM for contextual AI applications.Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year. Some projects may require a minimum of 16 consecutive weeks.

Research Scientist Intern, SLAM and Multimodal Sensing (PhD) Responsibilities:

• 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.

Minimum Qualifications:

• 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.

Preferred Qualifications:

• 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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