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Field
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sensor research and development for energy applications, with a focus on advanced manufacturing technologies. The MSA group consists of staff members with backgrounds in mechanical engineering, materials
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locomotion. Apply machine learning and machine vision algorithms to track body and limb movements. Use biomechanical modeling to analyze walking data and fit locomotion models. Operate a force sensor to
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university/spinout environment. This is a unique opportunity to work at the forefront of applied research and innovation, helping translate novel control algorithms and hardware prototypes into real-world
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pipelines, Mixed Reality Toolkit customization, and performance tuning under hardware constraints; collaborating on robot motion planning, path optimization, and sensor data processing algorithms
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system automation. Investigate and improve human-machine interaction frameworks for construction operations, including robotics, sensor-based communication, and real-time monitoring. Publish research
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radiative flux products using four sensors on EarthCARE - Observational diagnostics of cloud, precipitation, and radiation processes and evaluation of numerical models through multi-satellite synergy [Work
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-criteria, defining their formalization as fuzzy subsets, and characterizing their uncertainty; Integrating Machine Learning algorithms to better account for low-level sensor data (precipitation, wind-driven
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underlying pain and distressing symptoms in people who are no longer able to explain their suffering. The project will combine traditional assessment scales with sensor-based measurements, with novel analyses
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-making algorithm for autonomous vehicles. The work will involve sensor fusion, perception, trajectory prediction and test rig set-up, and experimental validation. Job Requirements: PhD Degree in Vehicle
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on creating accurate digital twins, improving anomaly detection models, and integrating visual data with spatial sensors like RGBD and LiDAR. This Research Engineer (Researcher 2) role offers the opportunity