About the Client

Our client is developing advanced interfaces at the intersection of neuroscience and intelligent systems. Their work focuses on building high-fidelity models of whole-brain function to deepen our understanding of cognition, behaviour, and biological computation.

They operate where neuroengineering, AI, and systems design converge — creating technologies that tightly link sensory processing, neural computation, and behaviour. A key long-term ambition is to enable data-driven alternatives to traditional animal testing by producing accurate predictive models of neural activity, while contributing to a future where advances in AI improve human insight and agency.

The Role

We are partnering with our client to identify a Neuroscientist with hands-on expertise in in vivo electrophysiology and implantable neural recording systems. This individual will play a critical role in shaping and executing the experimental foundation that supports the client’s development of interpretable, brain-inspired technologies.

This is a highly cross-disciplinary position at the interface of experimental neuroscience, engineering, and computational modelling.

Key Responsibilities

Experimental Design & Delivery
Lead in vivo electrophysiological studies using chronic and/or acute multi-channel implants
Develop and optimise protocols for neural recording, stimulation, and behavioural coupling
Validate new implant designs and refine surgical workflows alongside engineering teams
Record, curate, and analyse electrophysiological data across multiple brain regions
Implant & Systems Integration
Collaborate with hardware engineers on neural probe, headstage, and implant design
Integrate new sensors, amplifiers, and stimulation modules into experimental setups
Manage recording rigs, acquisition software, and associated data pipelines
Data Analysis & Interpretation
Process large-scale datasets using Python, MATLAB, or related analytical frameworks
Implement spike sorting, LFP analyses, and time–frequency signal processing
Work closely with computational neuroscientists to model and interpret neural activity
Cross-Team Collaboration
Partner with AI, embedded systems, and hardware teams to connect biological data with computational architectures
Support automation of experiments and behavioural monitoring
Contribute to strategic research design discussions, influencing both scientific and engineering roadmaps

Candidate Profile

The ideal candidate is a hands-on experimentalist with strong analytical skills, comfortable working across wet-lab and computational environments. They should be motivated by high-impact, long-term scientific challenges and thrive in cross-functional teams.

You will bring:

Extensive experience with in vivo electrophysiology
Strong problem-solving instincts and experimental rigour
A collaborative mindset and an interest in bridging neuroscience with technology development
Commitment to reproducibility, documentation, and scientific integrity

Requirements

PhD (or comparable experience) in Neuroscience, Neurophysiology, Biomedical Engineering, or related field
At least 1–2 years of hands-on experience with electrophysiological recordings in animal models
Proficiency with neural acquisition systems (e.g., Intan, Open Ephys, Neuropixels, Plexon)
Practical experience in signal processing, spike sorting, and time-series analysis
Strong Python, MATLAB, or equivalent technical skills
Familiarity with stereotaxic surgery, chronic implants, or neural stimulation systems
Solid grounding in neuroanatomy and experimental design

Preferred Experience:

Prior work developing or adapting neural recording hardware
Exposure to optogenetics, calcium imaging, or multimodal neurotech
Experience in research environments spanning both experimentation and computation
Publications or open-source projects in systems neuroscience or neurophysiology

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