- Lead the development and delivery of novel signal processing and machine learning models to interpret physiological signals, e.g. time series regression, classification and outliers detection
- Lead exploratory data analysis on complex time‑series datasets generated from clinical trials, internal studies, and external research databases
- Design and validate algorithms for denoising, signal demixing, and interpretation of neuromonitoring data
- Write high‑quality, well‑tested Python code that meets industry standards
- Collaborate with domain experts to translate clinical and physiological requirements into robust data analysis workflows
- Deliver signal processing methodologies ready for translation into medical device products
- Produce clear and insightful white papers, documentation, and visualisations for both technical and non‑technical stakeholders
- Participate in research planning by gathering requirements, scoping work items, and contributing to roadmap discussions
- Proven track record in applying machine learning / deep learning techniques for time‑series, physiological signals or continuous sensor data
- >4 years of experience in a research or applied data science role, ideally involving cross‑disciplinary collaboration with clinical or experimental teams
- A deep understanding of digital signal processing concepts such as sampling and quantisation, spectral analysis, etc
- Fluent in Python and expert in industry‑standard tools for version control, data engineering, CI/CD and reproducible research workflows
- Comfortable working in a fast‑paced, research‑driven environment with a strong sense of ownership and a willingness to learn and experiment
- Excellent written and verbal communication skills for conveying complex results clearly to technical and non‑technical stakeholders
- Experience with signal analysis and pipeline design for time series data in the context of wearable or medical products
- Hands‑on experience in software engineering
- Familiarity with regulated development processes (e.g. SaMD)
- Strong understanding of neurological and cardiovascular signals
- Strong background in biostatistics
- Strong understanding of the physical principles associated with optical spectroscopy, interferometry, and related techniques
- Company equity plan so all employees share in the success of the company
- Salary‑sacrifice pension scheme
- Private medical, dental and vision insurance (medical history disregarded)
- Group life assurance at 4× annual income
- Comprehensive mental health support, including unlimited access to 1:1 sessions with trained professionals
- Unlimited holiday allowance (+ bank holidays) and one week of remote working per quarter
- Free lunch twice per week via JustEat and free dinner on those days where you need to work later
- Twice weekly deliveries of fresh fruit and a comprehensive selection of snacks and drinks
- YuLife subscription, allowing you to turn your daily steps and meditation into discounts at a range of stores
- Access to Udemy for upskilling and professional development
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Senior Machine Learning Engineer - Greater London - Crane Venture Partners
Description
Location
London, UK
Employment Type
Full time
Location Type
On-site
Department
R&D
At CoMind, we are developing a non-invasive neuromonitoring technology that will result in a new era of clinical brain monitoring. In joining us, you will be helping to create cutting‑edge technologies that will improve how we diagnose and treat brain disorders, ultimately improving and saving the lives of patients across the world.
The Role:
As a Senior ML Engineer / Senior Data Scientist at CoMind, you will join a multidisciplinary team working at the intersection of neurophysiology, optics, machine learning, and signal processing. Your focus will be on analysing multidimensional time‑series datasets collected by our next‑generation neural sensor in both clinical trial and in‑house experimental settings.
You will play a key role in interpreting physiological and optical signals to derive actionable insights that inform product development and clinical decision‑making. Working closely with clinicians, neurophysiologists, physicists, and engineers, you will help lead algorithm and ML model development to extract meaningful metrics of brain function, improve signal quality through advanced denoising and demixing techniques, and validate signal fidelity in real‑world use.
At CoMind, all team members work at least 4 days per week from our new Kings Cross offices, plus a flexible work‑from‑home day.
Responsibilities:
Skills & Experience:
Nice to Have
Benefits:
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