The Meta Reality Labs Research Team brings together a world-class team of researchers, developers, and engineers to create the future of AR and VR. The Surreal Vision group at RL Research is seeking exceptional Research Scientists to research and help build the egocentric machine perception functionalities and digital twins of 3D scenes that will underpin future VR and contextual-AI-enabled AR devices.
This internship focuses on developing a learned model for motion analysis for swing sports as an alternative to heuristic, threshold-based methods. Research goals include: improving analysis accuracy, generalization across players and equipment, and generating interpretable feedback outputs. The intern will contribute to egocentric data collection using the team's simulator research setup, in addition to model development.
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 24 consecutive weeks.
Currently has, or is in the process of obtaining a PhD degree in the domain of Computer Science, Electrical Engineering, Robotics, Biomechanics, or a related field
Robust Python and hands‐on experience training models in PyTorch
Working knowledge of sequence/time‐series modeling (temporal CNNs, transformers, state‐space models,



HMM/CTC‐style segmentation)
Experience working with real sensor data, not just curated benchmarks
Comfortable running hands‐on hardware experiments with human participants in a lab setting
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Experience designing and executing your own data collections with wearable or motion‐capture hardware
Research experience with IMU‐based human activity recognition, pose/motion estimation, or wearable biosignals
Experience with surface EMG: filtering, rectification, envelope extraction, electrode‐shift and cross‐session variability
Familiarity with egocentric perception (Project Aria, Ego4D/Ego‐Exo4D, Aria Digital Twin) or multimodal sensor fusion
Background in sports biomechanics or motion analysis
self‐supervised or few‐shot learning for personalization
First‐author publications at CVPR/ICCV/ECCV/NeurIPS/ICLR, or in biomechanics and wearables venues
Plays swing sports - genuinely helpful for labeling and sanity‐checking feedback
Intent to return to a degree‐program after the completion of the internship
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📌 Research Scientist Intern, Wearable Sensing & Human Motion Analysis (Western Australia)
🏢 Meta
📍 Western Australia