About the role
Type:
Fixed-term or Full-time
Location:
London · On-site · May require occasional travel
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
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