Hardware Technician
Netholabs
Hardware Technician
Netholabs
AI-native CNS models for target discovery
Type: Full-time
Location: London and Brighton On-site
We are building integrated human motion-capture and neurophysiological recording systems for both controlled lab studies and naturalistic, in-the-wild data collection.
We need a reliable, hands-on assistant to support day-to-day operations at the London capture site. Working under the Hardware Systems Engineer, you'll prep and run sessions, keep the rigs and data in order, and make sure every capture follows the established protocols. This is an execution role: you'll run the standards someone else has set, and do it consistently.
Prepare rigs and equipment ahead of recording sessions
Run recording sessions following established SOPs
Handle participant setup and guide subjects through capture
Log sessions accurately and flag anything anomalous
Assist with rig assembly, teardown, and routine maintenance
Help set up and check multi-camera / multi-sensor configurations
Perform routine calibration checks under guidance
Keep data storage, file naming, and backups tidy and consistent
Maintain equipment inventory and flag restocking needs
Keep the capture space organized and session-ready
Support procurement and supplier logistics (orders, deliveries, returns)
Organized, reliable, and detail-oriented
Comfortable working hands-on with hardware and cabling
Able to follow technical protocols precisely and document as you go
Good communication; comfortable running sessions with participants
Exposure to motion capture, video, or physiological recording setups
Basic Python or scripting
Familiarity with structured data storage and file management
No prior mocap or neuro experience required; we will cross-train the right person.
Netholabs develops AI-native models that simulate biology and behavior to create “digital organisms.” It builds large, multi-modal datasets from preclinical CNS research and trains probabilistic, counterfactual AI models that can reason about biology and behavior. The goal is to enable rapid in silico experiments—ranking targets, simulating interventions, and prioritizing research programs—so pharmaceutical companies and research partners can accelerate target discovery and preclinical decision-making for neural disorders. The models start with mice and aim toward humans, functioning as neuro-behavioral foundation models. The company partners with pharma, academia, and technology players, and also integrates with other AI/data platforms while pursuing AI safety research by using whole-brain emulation to study goal formation and alignment in AI systems.
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