Biomechanics Engineer

Location:

Via Melen 83, 16152 Genoa, Italy

Contract:

Full-time, Permanent

Location:

Via Melen 83, 16152 Genoa, Italy
Contract Type:  Permanent, Full-time

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 movement analysis, biomechanical modelling, AI training, and clinical or experimental validation.
Develop and maintain pipelines for data cleaning, calibration, segmentation, quality control, annotation, and traceability.
Contribute to the development and maintenance of software pipelines for human sensing, teleoperation, and dataset generation, including synchronization, monitoring, logging, and data quality assurance.
Operate teleoperation systems during data collection, validation campaigns, and robot testing activities, contributing to the continuous improvement of teleoperation procedures and tools.
Support the creation of biomechanical digital models that link measured motion, forces, pressure, and physiological signals to interpretable indicators.
Collaborate with AI engineers, roboticists, clinicians, and hardware teams to connect human motion data with explainable models, robot control, and validation protocols.
Define and monitor technical quality metrics for acquisition repeatability, reconstruction accuracy, force estimation, data completeness, and model reliability.
Prepare technical documentation, experiment reports, acquisition protocols, and reproducible validation material.
Contribute to safe and compliant data handling, with attention to privacy, traceability, auditability, and interoperability requirements.

Requirements
Master’s degree in Biomedical Engineering, Robotics, Mechanical Engineering, Computer Science, Data Science, or a related technical field.
Practical experience with human motion acquisition, biomechanics, robotics experiments, or sensor-based data collection.
Strong understanding of kinematics, dynamics, signal processing, human movement analysis, and experimental validation.
Strong Python programming skills for data processing, analysis, visualization, and automation.
Practical software development experience in C++ for robotics, human motion analysis, sensor integration, and data-processing pipelines.
Familiarity with robotic software architectures, middleware and frameworks used for integrating sensing, control, teleoperation, and data-processing components.
Experience working with multimodal time-series data from sensors such as IMUs, motion capture, force plates, pressure platforms, EMG, or wearable devices.
Ability to design structured acquisition protocols, manage calibration procedures, and assess data quality and repeatability.
Interest in teleoperation, human-in-the-loop robotics, and human motion digitization technologies, with the ability to contribute both to software development and experimental activities.
Familiarity with human body models, biomechanical simulation, digital twins, or musculoskeletal modelling.
Ability to work effectively in laboratory environments and coordinate with technical, clinical, and robotics stakeholders.
Hands-on experience working with wearable sensing…