Cydar Medical innovates in the healthcare software space. We connect live images from the hospital operating rooms to the power of cloud computing. Our software guides physicians during complex endovascular procedures, which results in better outcomes for patients. Our product, Cydar EV, is used in innovative hospitals across Europe and the United States, providing us with a stream of data, which we use to constantly improve our algorithms. Our solutions address real clinical needs, and we are motivated by seeing how our algorithms improve patients’ lives. We are pushing the boundaries of technology and user experience to deliver a product which is revolutionising keyhole surgery.
- 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