Zebra medical vision is a leader in modern computer vision and deep learning practices.
The Algorithms team is in charge of creating cutting edge algorithmic products which detect and diagnose a wide variety of medical conditions from medical images.
These solutions help make medical diagnosis faster, more accurate and more accessible to millions of patients around the world.
As a researcher on the team, you will get a chance to work alongside some of the best minds in the field and implement the latest Deep learning and computer vision algorithms, in a multidisciplinary and dynamic environment.
- Research, design and develop deep learning and computer vision algorithms to detect a wide variety of medical conditions from image and textual data.
- Work with a multi-disciplinary team of medical doctors, engineers, and designers to deliver an end-to-end product: from the idea phase, through collecting and assessing the data, exploring algorithmic approaches, developing, testing, validating and integrating the algorithm in the production environment.
- Read and implement algorithms publications in the field of deep learning and computer vision, as well as publish your own work, and contribute to the community via conferences/meetups etc.
- Participate in long term research efforts, and build excellence in the field of deep learning for imaging data
- Contribute to the team’s methodologies, best practices and toolset, share your work and give/receive feedback from peers in the team
- MSC. in computer science, preferably in the field of machine learning/computer vision
- 3+ years of hands on development of complex machine learning models using modern frameworks and tools (ideally python based)
- 1+ year of hands on experience with Deep learning using common open source frameworks and tools (Keras, TensorFlow, Theano, Caffe etc.)
- Strong communication and collaboration skills
- Team player, positive and driven, fast learner
- PHD in machine learning - very strong advantage
- Experience in computer vision - very strong advantage
- Publications/public speaking experience in the field of Machine learning - strong advantage
- Experience in engineering, especially working with CI, docker, Hadoop, and distributed systems - strong advantage