Lead Mechatronics and Systems Engineer - Preclinical Research
Netholabs
- LocationLondon
- Work typeOn-site
- EmploymentFull-time
- Posted10 November 2026
- SourceArbeitnow job feed
Live checkFirst seen 2 h ago; still listed on Arbeitnow 10 min ago.
At a glance
- ContractFixed term
- Skills and toolsPython
Read from the ad by RoleFinder, with rules and an AI reading; the description is the source.
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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