Early application is encouraged as applications will be reviewed on a rolling basis
About the company
Healthcare systems globally are facing significant pressures, and epilepsy is a case-study of those challenges. More than 630,000 people in the UK live with the condition. Over 70% of routine EEGs are clinically inconclusive, and the average time to diagnosis is longer than a year. That leaves people waiting, and clinicians deciding without the evidence they need.
We built BioEP to close that gap. It analyses background activity in a routine EEG using eight predefined features drawn from peer-reviewed computational neuroscience, returning an objective rating in under five minutes. It works when nothing abnormal is visible, so it supports a decision precisely where conventional reading runs out. Our method is deterministic and explainable, not a black box or deep learning tool.
BioEP is UKCA-marked and has been validated across 15 NHS sites and more than 6,000 recordings. In June 2026 we raised £3M, co-led by Empirical Ventures and The FSE Group. That investment takes us through our FDA submission this year, extends BioEP into paediatrics and prognosis, and funds research on our next indication: traumatic brain injury.
Founded in 2018 Neuronostics has grown rapidly in the years since. In 2024 our international potential was recognised when we won the Epilepsy Foundation of the USA Shark Tank competition and with it a $125K prize. We've established transformative partnerships with leading industry players: Stratus Neuro (the leading US EEG services provider with 600+ hospital systems), Nervus (UK EEG services), and Neuroelectrics (advanced EEG hardware), creating immediate distribution channels and market access.
About the role
You will build the mathematical models and analysis pipelines behind our biomarkers, working with EEG data from our own studies and from clinical partnerships. Alongside epilepsy, we are developing the platform for traumatic brain injury, so there is scope to shape a new indication from the science upwards. You will contribute to study design, move research code into production-grade Python, and publish. Educated to PhD level, strong in Python, and pragmatic about finding the right level of complexity for the problem. A record of peer-reviewed publications is desirable for these roles.
We have two roles available: one focuses on refining and improving our existing biomarkers for epilepsy and the other focuses on developing novel biomarkers for Traumatic Brain Injury (TBI).
In this role you will:
- Develop an analysis pipeline for data emerging from clinical partnerships and our own technologies;
- Build mathematical models and computer algorithms for interrogating human brain data;
- Contribute to the design of clinical studies for evaluating both our existing epilepsy biomarkers and to develop novel biomarkers for TBI and other neurological conditions;
- Migrate and develop research codes (e.g. Matlab, R) into commercial grade codes in python;
- Work with our business development team to identify and evolve new market opportunities (including grant funding) and to contribute to bids for funding to support company activities;
- Contribute to the dissemination of key study findings through oral presentations and written publications;
- Promote Neuronostics as an organisation seeking to use data to enhance clinical diagnostics and management in neurology broadly.
About you
Essential
- A PhD in mathematics, computational neuroscience or other related area (or awaiting viva)
- Experience in a data analytical or a statistical role where you have delivered exciting data science solutions. Ideally in a healthcare setting already, but if not, you’ll be passionate about wanting to apply your skills in this setting.
- Experience in using a pragmatic approach to find the appropriate level of complexity for the problem at hand
- Proficiency in Python
- Experience with Data Science and Machine Learning tools
- Competency in structuring complex databases and writing efficient code to extract and interpret relevant data
- Ability to visualise data in meaningful and exciting ways
- Excellent written and oral communication skills, for example gathering user requirements and translating our technologies in simple ways. Stakeholder engagement is at the heart of what we do
Desirable
- Track record of peer-reviewed publications
- Understanding of data governance and GDPR
- Proficiency in programming languages such as Matlab, R and C#
- Experience in cloud database technologies (e.g. Firebase)
- Experience in network analysis of human brain data
- Experience of mathematical models of human brain networks
- Clinical networks ideally in TBI and/or epilepsy
What we can offer
- A role with genuine scope to shape a growing digital MedTech company and its products.
- A flexible working model that lets you work when you are most productive.
- A salary set according to experience, plus a performance bonus and the potential for share options.
- Company pension scheme: you contribute 2% and the company 7% on qualifying earnings.
- 25 days annual leave, plus public and bank holidays, plus an extra day off for your birthday.
- A collaborative environment where curiosity and initiative are encouraged and rewarded.
- A team combining scientific, clinical, technical and commercial expertise.
- Access to ongoing professional development.
- Regular staff events and company away days.
We work a hybrid model, blending time in the office with time at home. We expect regular time together in Bristol: a minimum of two days per week (with more desirable). We are based at Science Creates, a stone’s throw from Bristol Temple Meads Station.
How to apply
We would encourage you to get in touch early for an informal conversation about any of these roles. Contact recruitment@neuronostics.com to arrange this.
When you are ready to apply, send a CV and a covering letter setting out how your skills, experience and career plans fit what we are looking for via the 'Apply' button above (e: recruitment@neuronostics.com).
Applications will be considered on a rolling basis until each position is filled.
Competitive
