5 Billion people have no access to safe surgery and Touch Surgery is on a mission to solve that problem. If you’re looking for a real purpose behind what you do, this role is a genuine opportunity to make a difference.

The Computer Vision and Machine Learning team at Touch Surgery is dedicated to delivering the best user experience through cutting edge algorithms for surgical video. We are looking for smart, innovative and motivated individuals with Computer Vision and Machine Learning research & development backgrounds.

As a member of the R&D team you will be responsible for creating the next generation algorithms that power our products for the future operating room. You will work and develop systems detection, classification and tracking in video. Your work will contribute to the entire pipeline of our future products and you will perform research and development of new techniques that will have a strong impact on the company.

Detection and classification in images / video using the latest algorithms, where the data is available using deep learning.
Semantic understanding of scenes and the environment.
Research on detection and classification performance enhancement in difficult conditions with paucity of training data.




We will need you to have…

PhD in Computer Vision, Medical Image Computing or Machine Learning with a focus on detection and classification in images.
Strong publication record in relevant conferences or journals.
Experience with deep learning frameworks (Tensorflow, Caffe, Torch etc).
Evidence of designing / developing and training a deep convolutional network.
Experience and evidence of strong programming skills using C/C++ or high level languages like Python or Matlab.
We would like you to have, but not essential…

Experience with detection and classification problems transferring algorithms from research code to practical product implementation.
Experience working within the applied medical technology field.
Familiarity with the following technologies: Git, CMake, Debugging Tools, Continuous Integration.
Experience with cloud platforms for training deep neural networks.
Low level experience with GPU programming.
Experience working in a fast paced, tight-knit multi-disciplinary team

Educational level:

Ph. D.

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