- Working on a range of problems in medical image analysis: image segmentation, classification, spatiotemporal analysis, object detection, registration, etc.
- Experimenting with modern machine learning methods to solve major challenges. The work will focus on techniques which will be incorporated into our planning and registration software.
- Writing and maintaining in-house machine learning packages, following best practices in software development and packaging.
- Maintaining and improving data pipelines.
- Collaborating closely with software engineers and the QA team to ensure the highest quality of developed solutions.
- Managing projects from concept to delivery, adhering to design requirements and deadlines.
- Keeping up to date with the latest developments in machine learning.
- Presenting at internal meetings, as well as external meetups and conferences.
As the ideal candidate you will have a sound understanding of modern machine learning techniques. You will be passionate about applying these techniques to solve real-world problems; rigorous when prototyping and experimenting; and able to express your solutions in high quality code. As a member of the Science team at Cydar Medical, you will be expected to work collaboratively, sharing your ideas with others and learning new techniques and skills.
- experience using Python deep learning frameworks (TensorFlow, PyTorch, etc.)
- proficiency in Python
- experience applying deep learning methods to real-world problems
- strong analytical and problem-solving skills
- knowledge of good programming practices and software development principles
- permission to work in the United Kingdom
- image/volume processing libraries, e.g. ITK, VTK, OpenCV, scikit-image
- modern cloud infrastructure, e.g. AWS or GCP.
- git or other version control systems
- Python packaging tools, e.g. virtualenv, pipenv, PyPI, poetry, etc.
- university degree in computer science, software engineering, maths, or another relevant field
- algorithm design and development