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Masters' or PhD's degree in Robotics, Computer Vision, Machine Learning, Artificial Intelligence, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation (e.g. physics, aerospace engineering.
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0 years of related experience with a Bachelor's degree in Aerospace Engineering, Computer Science, Computer Engineering, Electrical Engineering, Physics, Imaging Science, Optical Science/Engineering, Robotics, Mechatronics Engineering or other related discipline.
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Bachelor’s Degree, or higher-level degree, in Computer Science, Engineering, or related quantitative field that demonstrates knowledge of AI, machine learning, optimization, random processes, sensor signal processing, or mathematical modeling.
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PhD in Computer Science, Electrical Engineering, Robotics, or a closely related field, with a focus on mapping, localization, or SLAM. Hands-on experience with sensor calibration, data fusion algorithms, and the integration of various sensors (e.g., LIDAR, radar, cameras) for vehicle localization.
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Masters degree in the one of the following; computer science, machine learning, computer engineer. Bachelor degree in the one of the following; computer science, machine learning, computer engineer.
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Master's or PhD degree in Aerospace Engineering, Electrical Engineering, Computer Science, Robotics or a related field. Implement sensor fusion techniques to integrate data from multiple sensors such as GNSS, IMU, LIDAR, radar, sonar and cameras to enhance the accuracy and robustness of vehicle navigation where applicable.
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Experience with sensor calibration, sensor fusion, state estimation, and SLAM (Simultaneous Localization and Mapping) techniques. Design, develop, integrate and test inertial navigation systems (INS), GNSS products, visual navigation, and other related technologies for autonomous military vehicles (UAS, spacecraft, missiles, ground vehicles, underwater vehicles etc.
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Proven experience in developing Navigation and Localization algorithms for autonomous vehicles, robotics, drones, maritime vehicles or similar application. Develop algorithms for navigation, localization, and positioning systems, including Kalman filters (Extended-KF, Unscented-KF, Ensemble-KF, Iterated-EKF, Gaussian Sum Filter) and other estimation methods using various programming languages.
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Bachelor's degree in Computer Science, Electrical Engineering, Robotics Engineer or a related field. Must have experience working with multi-camera systems, visual odometry, simultaneous localization and mapping (SLAM), LiDAR, IMU.
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Deep technical knowledge in one or more of the following areas: robotics, embedded systems, computer vision, LiDAR, deep learning, guidance navigation and control. Background in lidar or vision data processing, computer vision algorithms, and robotic state estimation.
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Bachelors degree in computer science, business, GIS or other relevant geospatial or data science related field, masters preferred. Knowledge of/Experience with remote sensing, lidar and imagery services desired.
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Bachelors or master's in Computer science, Data Science, or a related field. Experience in delivering AI/ML, statistical solutions on geospatial data i.e., Satellite , Lidar etc.
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Training in perception (computer vision/image processing, LIDAR and/or radar) software solutions for various intelligent system applications. Requires a Masters or a PhD in Data Science, Computer Science, Computer Engineering, Electrical Engineering, Mechanical Engineering, or related field with related work experience.
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An understanding of computer vision, mobile autonomy or LiDAR data processing. Our team of experts in computer science, AI, robotics and machine learning is world-class, and together they’re solving the most exciting and important technological challenges of our times.
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Interested in Computer Vision, Augmented Reality, Virtual Reality or Spatial Computing. Working on manual iOS and visionOS testing, you will be responsible for assessing the quality of new and existing AR and Spatial Computing algorithms which run on devices with LiDAR sensors.
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