Advance the future of human-computer interaction within Augmented, Mixed, and Virtual Reality by bridging machine learning systems for hand pose and gesture recognition with human biomechanics and ergonomics research.
Requirements
- Proficiency in Python (pandas, numpy, matplotlib, seaborn, etc.) and experience with statistical analysis and data quality pipelines.
- Demonstrated expertise with biomechanical research methods (motion capture, EMG, force sensors, kinematics).
- Proven track record of designing and executing human participant studies.
- Familiarity with Linux environments, experimental design, and research lab equipment setup/maintenance.
- Experience with deep learning frameworks (PyTorch, TensorFlow) for gesture or pose recognition.
- Knowledge of ergonomics, human anatomy, and motor control in applied computing contexts.
- Hands-on experience integrating ML models with physical prototypes.
Responsibilities
- Design, plan, and conduct human-subject studies exploring natural motion, biomechanics, and user comfort in AR/VR input systems.
- Lead data acquisition, annotation, and quality assurance for machine learning hand pose and gesture recognition models.
- Develop and execute ML training, evaluation, and experimentation pipelines, including performance analysis and failure investigations.
- Collect and analyze biomechanical and physiological time-series data (kinematics, EMG, force), applying statistical and computational methods to extract insights.
- Build and maintain data processing and visualization pipelines using Python (pandas, matplotlib, etc.), Matlab, or R.
- Integrate and synchronize sensors and research equipment (motion capture, EMG, force plates, accelerometers, etc.) with ML workflows.
- Partner with engineers and prototypers to ensure ML models and device designs are aligned with human factors principles.
Other
- PhD (or equivalent experience) in Computer Science, Machine Learning, Biomechanics, Mechanical Engineering, Human Factors, or related field.
- 5+ years of experience in machine learning operations, data analysis, and visualization.
- Strong technical writing and communication skills, with a record of publishing or presenting scientific research.
- Ability to translate research requirements into clear instructions for moderators, participants, and engineering teams.
- Self-driven and adaptable, with strong problem-solving and experimental analysis skills.
