Lead Mechatronics and Systems Engineer - Preclinical Research

Type: Fixed-term or Full-time Location: London

• On-site
• May require occasional travel Compensation: £65–85k/year, in accordance with experience THE ROLE We are building integrated human and non-human motion-capture and neurophysiological recording systems for both controlled lab studies and naturalistic, in-the-wild data collection. We are looking for an experienced researcher engineer that is hands-on to own the London capture site across both lab and field settings: set up and run the hardware, import and enforce best-practice capture protocols, and ensure every session executes reliably and reproducibly. This is an operational role: you'll take defined capture standards and make them run at scale, not design the science.

RESPONSIBILITIES

EXPERIMENTAL OPERATIONS

• Implement and maintain streamlined, minimal capture protocols
• Import and operationalize best-practice standards for human mocap
• Prepare and run recording sessions
• Maintain clear SOPs and documentation
• Ensure sessions are reproducible and well logged HARDWARE & SYSTEMS
• Set up and maintain motion-capture and neurophysiological recording systems
• Integrate all devices on a shared clock (video, kinematics, physiological streams)
• Troubleshoot signal, sync, and capture-quality issues
• Assemble and maintain multi-camera / multi-sensor rigs
• Manage equipment inventory, calibration, and camera setup INFRASTRUCTURE
• Oversee lab layout and capture-space setup
• Maintain structured data storage, formats, and backups
• Coordinate procurement and supplier communication REQUIREMENTS Core (essential)
• Experience with human motion capture (marker-based, markerless/computer-vision, or IMU-suit systems)
• Multi-camera calibration and time synchronization
• Strong hardware troubleshooting ability
• Comfortable with embedded systems
• Basic Python scripting
• Organized and systematic; disciplined about documentation and reproducibility Valued
• Hand / finger kinematics capture and video pipelines
• Structured data formats (e.g. HDF5) and reproducible data logging
• Experience with physiological recording systems (EEG or similar), or willingness to cross-train