Lead Mechatronics and Systems Engineer – Preclinical Research

Full Time Onsite Senior £65k–85k/yr London Just posted

Netholabs

Netholabs
📍 London Senior United Kingdom
ragsystems engineer

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

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