Neuroscientist; Electrophysiology & Implant Systems

Location:

London, UK (Hybrid/On-site)
Type:
Full-time
Salary:
Competitive + Equity Options

Netholabs is building the interface between brains and intelligent machines. Our mission is to achieve functional whole-brain emulation — a foundation for understanding consciousness, cognition, and control in living systems.

We operate at the convergence of neuroengineering, AI, and systems design — developing technologies that close the loop between perception, computation, and behaviour.

Our long-term vision is to eliminate animal testing by developing accurate, data-driven brain models, while ensuring that as AI becomes more capable, human agency and understanding grow alongside it.

We are seeking a Neuroscientist with hands-on experience in in vivo electrophysiology and implantable recording systems. You will play a key role in the design, validation, and execution of neural experiments that support Netholabs’ efforts to build interpretable, brain-inspired technologies.

This position bridges neuroscience, engineering, and computational modelling — ideal for a scientist who thrives in cross-disciplinary environments and enjoys working at the edge of experimental and theoretical research.

• Plan and perform in vivo electrophysiology studies using implanted multi-channel recording systems (chronic or acute).
• Design protocols for neural signal acquisition, stimulation, and behavioural interfacing.
• Validate implant designs and optimize surgical procedures in collaboration with engineers.
• Record, preprocess, and analyze electrophysiological data from diverse brain regions.

• Collaborate with engineers on the design and testing of neural probes, headstages, and implant hardware.
• Integrate new sensors, amplifiers, and stimulation systems into lab workflows.
• Manage and maintain recording rigs, software interfaces, and data pipelines.

• Process large-scale neural datasets using Python, MATLAB, or related toolkits.
• Develop and apply spike sorting, LFP, and time–frequency analysis methods.
• Collaborate with computational neuroscientists to interpret and model recorded activity.

• Work closely with AI and embedded systems engineers to connect biological data with computational models.
• Contribute to experiment automation and behavioural monitoring systems.
• Participate in research design discussions that inform both engineering and neuroscience directions.

You’re a scientist–builder who is as comfortable at the bench as at the workstation. You bring rigor, curiosity, and precision to your work — and are excited by the opportunity to merge neuroscience with technology development.

• Deep hands-on experience with in vivo electrophysiology.
• Motivated by long-term, high-impact research.
• Enjoy solving experimental and technical challenges collaboratively.
• Value open science, reproducibility, and creative problem-solving.

• PhD (or substantial experience) in Neuroscience, Biomedical Engineering, Neurophysiology, or related field.
• Minimum 1-2 years of experience with electrophysiological recordings in animal models (rodents or primates).
• Proficiency with neural data acquisition systems (e.g., Intan, Open Ephys, Neuropixels, Plexon).
• Experience with neural signal processing, spike sorting, and time-series analysis.
• Skilled in Python, MATLAB, or equivalent analysis languages.
• Familiarity with stereotaxic surgery, chronic implants, or neural stimulation setups.
• Strong understanding of neuroanatomy and experimental design principles.

• Experience developing or modifying neural recording hardware or implant designs.
• Familiarity with optogenetics, calcium imaging, or multimodal integration.
• Prior work in hybrid wet-lab / computational settings.
• Publications or open-source contributions in neurophysiology or systems neuroscience.

• A research-driven environment integrating neuroscience, AI, and hardware development.
• Access to state-of-the-art tools and facilities for electrophysiology and neuroengineering.
• Opportunities to collaborate across hardware, AI, and computational teams.
• Competitive salary with meaningful equity participation.
• A culture of rigor, transparency, and long-term mission alignment.

Please send a short email introducing yourself — along with your CV, publications, or portfolio — to  .

Include links to datasets, papers, or open-source work if relevant.