Required Qualifications:
Develop and Implement Deep Learning Models: Design, train, and optimize machine learning and neural network models for applications in computer vision and robotics, ensuring high performance and accuracy.
Enhance Geometric Computer Vision Techniques: Apply advanced algorithms for tasks such as visual odometry, feature extraction, and object recognition, leveraging geometric principles to improve system robustness and accuracy.
Implement SLAM (Simultaneous Localization and Mapping): Develop and optimize algorithms for real-time environment mapping and robot localization, ensuring seamless navigation and object tracking in dynamic environments.
Integrate Optical Flow and Visual Navigation Systems: Design and integrate optical flow methods to enable precise motion estimation, visual-based navigation, and dynamic obstacle avoidance for autonomous systems.
Leverage Geometric Algebra for Advanced Computing: Utilize geometric algebra (Clifford algebra) to improve the efficiency and accuracy of spatial transformations, rotations, and other geometric operations in computer vision and robotics tasks.
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