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 mission is to improve early detection and diagnosis of cancer in gastroenterology though 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 Hospital. We believe Odin Vision’s technology is set to revolutionize clinical practice and we are looking for smart and passionate people to join our team.
As a Machine Learning PhD intern at Odin Vision, you will explore and develop cutting edge machine learning techniques applied to cancer detection and diagnosis in images. You will work alongside our talented team of researchers and engineers to develop prototype and clinical software.
You must be able to work well in a multi disciplinary team and have strong communication skills. You should be at least one year into your PhD studies and be able to commit at least 16 hours per week part time for a minimum of 6 months or full time for at least 3 months. You should have a passion for technology, healthcare and improving the lives of others.
• Responsible for researching, developing and testing machine learning solutions.
• Generate creative, novel solutions to challenging problem
• Review the latest advances in the field and propose novel applications.
• Generate reports, documenting your work and results.
• Studying a PhD in, Computer Science, Medical Imaging, Computer Vision, Machine Learning or similar related field.
• Experience of developing and delivering machine learning focused projects.
• Experience with deep learning tool kits (Pytorch, Keras, TensorFlow, Caffe)
• Programming experience, Python, C++.
• Knowledge of medical imaging, computer vision or experience working with video data is a bonus.