Biomechanics Engineer
Pubblicato il 07-09-2026 - Generative Bionics in Genova
About Us
Generative Bionics is a deep-tech company building humanoid robot platforms to deploy human-centered Physical AI. We design intelligent, capable machines that work alongside people in real-world environments, developed in Genoa, Italy.
Role
We are looking for a Biomechanics Engineer to support the development of data-driven rehabilitation and humanoid robotics technologies. The role focuses on acquiring, synchronizing, validating, and interpreting multimodal human motion data, and on transforming these measurements into reliable human body models and biomechanical digital representations.You will work at the intersection of sensorized data acquisition, biomechanics, robotics, and AI. You will help design and operate measurement workflows using wearable sensors, motion capture, force and pressure platforms, EMG, and smart shoes. The goal is to build high-quality datasets and patient- or subject-specific models that connect measured movement, forces, pressure,
and neurophysiological signals with interpretable analytics and safe robotic interaction.The role also includes contributing to our teleoperation technologies, both through software development activities and through hands-on operation of teleoperation systems during data collection, validation campaigns, and robot testing.The ideal candidate is hands-on, rigorous, and comfortable working with complex experimental setups, human movement data, and multidisciplinary teams.
Responsibilities
- Design, prepare, and execute human motion data acquisition sessions using wearable sensors, motion capture systems, force/pressure platforms, EMG, smart shoes;
- Validate wearable sensing systems against laboratory reference measurements (e.g., motion capture, force platforms), define benchmarking methodologies, and report quantitative performance metrics;
- Synchronize and validate multimodal kinematic, dynamic, pressure, and neurophysiological data streams;
- Build, curate, and document structured datasets for human