At Sensyne Health we combine technology and ethically sourced patient data to help people everywhere get better care. To do this, we have created a unique partnership with the NHS that delivers a return to our partner Trusts and unlocks the value of clinical data for research while safeguarding patient privacy. Alongside this, we develop clinically validated software applications that create clinician and patient benefit while providing highly curated data. Our products include vital-signs monitoring in hospitals and patient-to-clinician apps to support self-care and remote monitoring of gestational diabetes and chronic diseases such as COPD and heart failure.
We use our proprietary clinical AI technology to analyse ethically sourced, clinically curated, anonymised patient data to solve serious unmet medical needs across a wide range of therapeutic areas, enabling a new approach to clinical trial design, drug discovery, development and post-marketing surveillance.
Our Life Sciences team is currently expanding to bring further expertise into a cross functional environment. The aim is to drive the next generation of innovation for better patient outcomes, whilst harnessing some of the industry’s most progressive AI approaches. This is centred on data-efficient machine learning algorithms. The nature of our team is collaborative with an emphasis on genuine passion for healthcare. Whilst the current team already has three clinically validated products, the new members will be part of a sub-team focusing on innovating new product lines. The roles are research based with high potential for professional growth, support towards our business goal and ongoing contribution to the development of healthcare by working in a stimulating environment focused on improving patient outcomes.
As part of our visualisation and interpretation team this individual will work closely with our Clinical and Data Science/Machine Learning team to interpret and generate novel insights from our machine learning results and to accelerate the clinical workflow. This includes development of novel clinically relevant interpretation tools based on your data science and machine learning knowledge, and in close collaboration with our wider team; implementation of visualisations which ease the clinical workflow and development and maintaining of a scalable code base which can be used for various customer projects.