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Field
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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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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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, the selected researchers will deal with: Research & Development: Designing, developing, and implementing state-of-the-art machine vision and deep learning algorithms to analyze complex image and sensor data
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satellite datasets and employ near-real-time server-side algorithms for time-series analysis and the generation of value-added geospatial maps. To enhance the sustainability performance and competitiveness
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closely with a small, dedicated team, you will: Design and implement SLAM-based navigation algorithms for GPS-denied forest environments (45%) Develop multi-sensor integration software for LiDAR, cameras
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Professor Kalina Yacef. These projects explore how multimodal data from online platforms and sensor-based environments can be harnessed to enhance learning at scale. Research directions include designing
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techniques; b) Practical experience in experimental data acquisition, particularly with biosignal systems and physiological sensors; c) Experience in data curation and management, including cleaning
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research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins
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settings. Our project focuses on knitting of functional yarns through which knitted wearable with sensors and electronics are achieved in a single knit. Our knitted wearable solutions aims for real world
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. Develop and implement control algorithms for distributed multi-agent system operations and spacecraft-based robotic manipulation. Perform research on spacecraft dynamics and control, including trajectory