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in collaboration with international research and industrial partners. The position requires software development within the topics of navigation, sensor fusion, Kalman filtering and gravity field
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computationally efficient numerical structural models. To support the condition (state) assessment, the project will also explore the use of advanced estimators (e.g., Kalman Filter) or Machine Learning models
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experience in ROS/ROS2 and Linux environments. Familiarity with LiDAR/camera calibration, sensor error modeling, and basic filtering algorithms (e.g., Kalman, particle filters). Strong communication skills and
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experience in ROS/ROS2 and Linux environments. Familiarity with LiDAR/camera calibration, sensor error modeling, and basic filtering algorithms (e.g., Kalman, particle filters). Strong communication skills and
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) Mathematical Modeling, Optimization, and Simulation Classical Image Processing and Machine/Deep Learning Probalistic Sensor Data Processing ( Kalman Filter, etc.) What you can expect A dynamic work environment