Research Scientist Intern: Wearable Motion Analysis

Meta; Redmond; On-site; AUD 49,000 - 78,000; Part time

Job summary

Meta's Reality Labs Research team invites exceptional researchers to join the Surreal Vision group as an internship focused on learning-based motion analysis for swing sports. You will work on egocentric perception, data collection with wearable or motion-capture hardware, and model development using PyTorch in a lab setting.

Ideal candidates are pursuing a PhD in CS/EE/Robotics/Biomechanics, with strong Python and PyTorch skills, experience with sensor data, and a track record of publications

Qualifications

• Pursuing a PhD in CS, EE, Robotics, Biomechanics or related field.
• Strong Python and PyTorch experience.
• Experience with real sensor data and lab-based experiments.
• First-author publications at CVPR/ICCV/ECCV/NeurIPS/ICLR or biomechanics wearables venues.
• Willingness to label data for swing sports and verify feedback.

Responsibilities

• Develop a learned model for motion analysis for swing sports.
• Contribute to egocentric data collection using the team's simulator and wearable sensors; assist with model development.
• Train and evaluate models in PyTorch; explore time-series models (temporal CNNs, transformers, HMM/CTC).
• Aim for generalization across players/equipment and provide interpretable feedback outputs.
• Assist with data collection and experiments involving human participants in lab settings.

Skills

Python

Time-series modeling

Motion analysis

Data collection

Research collaboration

Education

PhD candidate in CS/EE/Robotics/Biomechanics

Tools

PyTorch

Job description

Meta's Reality Labs Research team invites exceptional researchers to join the Surreal Vision group as an internship focused on learning-based motion analysis for swing sports. You will work on egocentric perception, data collection with wearable or motion-capture hardware, and model development using PyTorch in a lab setting.

Ideal candidates are pursuing a PhD in CS/EE/Robotics/Biomechanics, with strong Python and PyTorch skills, experience with sensor data, and a track record of publications