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Field
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with the latest sensors (camera and LiDAR sensors), is available for the work. What you will do Development of algorithms for 3D multi-object tracking based on heterogeneous sensor data fusion (standard
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100%, Zurich, fixed-term The Computational Design Lab is an interdisciplinary research group at ETH Zurich, led by Prof. Dr. Bernd Bickel . We develop novel algorithms and next-generation
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
applications for air quality management. This will include acquiring datasets related to multiple air quality sensors from diverse data sources, develop open-source, easy to use tools to compare different types
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and collaborative research focused on incorporating sensing technology in the early childhood education space. “Sensing technology” refers to tools that use sensors to acquire information about human
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on integrating sensor-driven data streams and historical datasets into the hybrid digital twin framework, thus enhancing the reliability, safety, and efficiency of SDVs throughout their lifecycle—from design and
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in the live organism to study e.g. immune responses or cancer development. Moreover, using molecular sensors we also aim to read out cellular functionality in vivo e.g. metabolic reprogramming in
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multidisciplinary topics from signal processing to machine learning to algorithm design with a focus on sensor systems. ARL is an authorized DoD SkillBridge partner and welcomes all transitioning military members
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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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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 3 months ago
Is the Main Topic in Virtual and Augmented Reality and Physical Activity Research: A Bibliometric Analysis. Sensors (Basel). 2023 Mar 9;23(6):2987. doi: 10.3390/s23062987. PMID: 36991699; PMCID
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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