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Field
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will be embedded in the ResiRob consortium (which brings together mechanical design, embedded sensors, control, materials science) and will work in close collaboration with teams specializing in
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. Development of real-time optimization algorithms and model predictive control (MPC) strategies for adaptive process management. Addressing data sparsity and data quality issues in industrial process data
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, reliability, and consistent behavior. Learning-based controllers can achieve high performance in complex and uncertain environments, yet ensuring predictable operation under distribution shifts, sensor noise
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sensors systems, 2D/3D cameras and LiDAR, inertial sensors, radar technologies, GPS, and calibration methods Real experience in designing, implementing and testing of robust, efficient perception algorithms
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of Oxford. The post is funded by United Kingdom Research and Innovation (UKRI) and is for 24 months. The researcher will develop 3D mapping and reconstruction algorithms with relevance to mobile robotics
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and communication systems. You will work with real measurement data and participate in both algorithm development and experimental validation. You will collaborate with industrial and academic partners
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will be responsible for programming and maintaining gait exoskeleton systems, developing and implementing real-time control algorithms in C/C++, Python, and Simulink, as well as integrating feedback from
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We are seeking an outstanding candidate for a Postdoctoral position in the field of robot motion and control algorithms for soft material handling, starting immediately. We are looking for a highly
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learning algorithms and creating predictive models. This role will contribute to evidence-based processes and procedures for program quality review and assessment of outcomes data as well as develop
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offer an exciting postdoctoral position, in collaboration with Demcon, focusing on off-road SLAM using lidar, camera, and IMU. Do you have a deep understanding of semantic segmentation, SLAM, sensor