Sensyne Health is hiring a

Machine Learning Researcher

Oxford, United Kingdom

About Us

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.

The Team

Our Discovery 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.



  • Building and implementing Machine Learning (ML) solutions to provide accurate, timely, and actionable intelligence to support business decision-making within life sciences
  • Support and guide other researchers in learning about, applying and delivering product features driven by ML techniques.
  • Help develop robust model training and data infrastructure to support continuous optimisation of ML-driven approaches.
  • Publish research results in national and international conferences and scientific journals.


  • PhD degree in Computer Science, Machine Learning or a related quantitative field
  • Hands-on experience using machine learning
  • Expert coding skills (Python, C++ are a plus)
  • Strong academic and research track record demonstrated through publication of papers in top scientific conferences and/or journals.
  • Hands-on experience using one of the following deep learning libraries: Tensorflow, PyTorch, Theano or similar.
  • Experience of analysing clinical/healthcare data is considered a bonus


  • Company share option scheme
  • 5% employer matched Pension scheme
  • BUPA Health Insurance including Partners and Children cover
  • Free Gym Membership
  • Cycle to work scheme
  • A challenging and fun environment that rewards results