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