About the job
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ResponsibilitiesIn a senior software engineering role, you will research and develop imaging algorithms and collaborate with other domain experts to bring our innovations from concept to the product:
- Build and optimise algorithm for image segmentation, classification, etc. e. g. segmentation/classification of the tissue specimen on the glass slides or whole slide image(WSI).
- Good understanding of color spaces( RGB, HSV, etc. )
- Collaborate with image quality evaluation team to continuously improve the WSI scan quality and algorithm performance across a wide range of specimen types.
- Develop and maintain end to end algorithm models for imaging parameters and sequences in order to develop intelligent routines based on the content in the specimens.
- Collaborate with platform software engineers to co-optimize algorithms and software implementation.
- Guide junior engineers and help them achieve their goals in image processing and analytics
- Degree in EE/Computer Science/Physics with relevant emphasis in image processing or signal processing.
- 2-6 years relevant hands-on experience including one Research & development cycle transferring an image acquisition and processing pipeline to a platform.
- Solid understanding of key image processing algorithms, color space and problems around image quality.
- Solid understanding of mathematics (probability, algebra, calculus, etc. )
- Excellent programming skills in C/C++ and Python are required, knowledge of machine learning libraries is essential
- Familiarity with sensor/camera component interactions
- Degree in EE/Computer Science/Physics with relevant emphasis in image processing, optics, or signal processing.
- Track record of innovative thinking as evidenced by patents and peer-reviewed publications.
- Understanding and preferably hands-on experience with deep learning frameworks and Neural Network processing architectures.
- Experience with compute engines and tools for Graphics, Computer Vision, ML/AI.
- Solid understanding of Statistical modelling, Probability and Stochastic methods
