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Field
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integrating visual data with spatial sensors like RGBD and LiDAR. This Research Engineer (Research Technician 2) role offers the opportunity to work across the full stack of data collection, model training
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calibration of force sensors (FSRs), inertial sensors (IMUs), and distance sensors (e.g., LRF or depth camera). ii) Assisting in the design and testing of miniaturized and low-power electronic circuits
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findings regularly. Prototype algorithms, validate outputs, and document methods clearly Collaborate asynchronously with an international team, present findings regularly Experience with remote sensing
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interact with the world around us. However, the power requirements and carbon emissions of AI are equally dramatic: training a single state of the art algorithm has the same carbon footprint as the lifecycle
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vision algorithms such as YOLO on static and mobile multi-sensor detection and sensing platforms. Support characterization measurements and associated data analysis of a new generation of scintillation
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utilizing existing and upcoming sensor deployments. The opportunity will include a range of activities and experiences including data collection, image analysis, workflow/algorithm development, sensor testing
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communication Autonomous driving algorithms and technologies (e.g. vehicle control, path planning, scheduling) and sensors (e.g. lidars, radars, cameras, and GNSS) High-level integration of autonomous driving
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vehicle (AV), allowing for automated detection, prediction, mapping, and planning. During the vehicle’s operation, data is obtained through a myriad of sensors in an AV—including RADAR, LIDAR, cameras, and
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skills and motivation to implement algorithms and test them in practice on large-scale problems. Programming Skills: You are proficient in at least one scientific programming language (such as Python
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. Successful re-development for end-of-life composites could enable reuse in other structural applications. This PhD will investigate the development of hierarchical Bayesian algorithms to capture