£50000 - £55000 per annum + Company Benefits
11 days ago
Machine Learning Researcher (Medical Devices, Time Series)
We are partnered with a disruptive Healthcare Tech company that is currently seeking a talented Machine Learning Researcher (Medical Devices, Time Series). This organisation is based in Oxford however supports fully remote work. This is a tech-for-good company utilising cutting-edge AI technologies to meet healthcare needs and improve patient wellbeing.
This Machine Learning Researcher will be comfortable programming (e.g., Python, C++, etc) and have a background in a relevant Machine Learning field (e.g., Deep Learning) and experience working with RNNs is ideal. You will take a hands-on approach in creating ML frameworks and have a central role in processes end to end. Your research and innovations will have a significant impact on patient wellbeing and improving lives. You will have the opportunity to publish your research at established conferences and journals on a national and international level.
What we can offer a Machine Learning Researcher (Medical Devices, Time Series):
- Company shares scheme
- Opportunity to publish research nationally and internationally
- Autonomy to explore data and generate Machine Learning solutions to medical problems
- Scope for rapid progression and to work with cutting edge technologies
- Fully remote working from anywhere within the UK
Apply now for immediate consideration on this excellent opportunity!
Understanding Recruitment is acting as an employment agency for this vacancy
Key Skills: Machine Learning Researcher (Medical Devices, Time Series); Research, Researcher, Data Scientist, Python, R, Backend, Bayesian, Hypothesis Testing, Isometric Testing, Data Analysis, Statistics, Biostatistics, SQL, NoSQL, Shiny, Graph database, Knowledge Graph, Tidyverse, Machine Learning, AI, Artificial Intelligence, Computer Science, Publications, Deep Learning, Algorithm, Algorithms, Survival Analysis, Enrichment Analysis, Tensorflow, Pytorch, PHD, Msc, masters, Bsc, bachelors, Health, Healthcare, Bayesian, AWS, Azure, Cloud