London, United Kingdom
1 in 2 people will be diagnosed with cancer in their lifetime. Today, Colorectal Cancer (CRC) is the second most common cause of cancer related deaths in the UK. However, if it is diagnosed early, the treatment is simple and effective, with high survival rates. Odin Vision’s mission is to improve early detection and diagnosis of cancer in gastroenterology through artificial intelligence.
Our award winning technology has been developed by experts at University College London in conjunction with world renowned clinical opinion leaders at University College London Hospital. We believe Odin Vision’s technology is set to revolutionize clinical practice and we are looking for passionate people to join our team.
As a Junior Research Scientist at Odin Vision, you will help to design, implement, and validate our in house machine learning frameworks. You will work alongside our talented team of researchers and engineers to develop prototype and clinical software. You will collaborate with academics, industrial researchers and clinical experts in short development sprints. You must be able to work well in a multi disciplinary team and have strong communication skills. You should be familiar with state of the art machine learning. You should be able to work in a fast paced, dynamic environment and have a passion for technology, healthcare and improving the lives of others.
- Responsible for implementing, developing, testing, optimizing and validating machine learning frameworks for image and video data
- Tasks include image segmentation, object detection, classification, video/temporal machine learning
- Work with a multidisciplinary team
- Work in a lean / agile development environment
- Generate reports, document your work and results
- An MSc or PhD in Machine Learning, Medical Imaging, Computer Vision or Computer Science
- Experience of developing and delivering machine learning focused projects
- Experience with deep learning tool kits (Pytorch, Keras, TensorFlow)
- Knowledge of machine learning methods such as CNN, RNN, Generative networks, Explainability/interpretability, meta learning, unsupervised learning, anomaly detection
- Programming experience: Python, C++
- Experience in medical imaging, computer vision or working with video data is a bonus