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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | about 18 hours ago
. Interoperable medical devices being investigated may include wearable sensors (e.g., photoplethysmography for pulse oximetry and blood pressure measurements, inertial measurement units for gait and movement
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interest since 2000. It allows us to better plan our cities, and new approaches have been made possible with the widespread use of smartphones carrying several different sensors. As a matter of fact, in most
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on applied research in neuromorphic systems across three pillars: sensors, algorithms, and platforms, and will collaborate closely with its partner ICNS at Western Sydney University, which was also established
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on applied research in neuromorphic systems across three pillars: sensors, algorithms, and platforms, and will collaborate closely with its partner ICNS at Western Sydney University, which was also established
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Responsibilities: Design and implement advanced AI/ML models for healthcare applications, including predictive analytics and generative AI solutions. Develop and validate digital phenotyping algorithms using
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, manufacturability, and operational performance in pipeline environments. B. Defect Detection & Multimodal ML Oversee the development of vision-/LiDAR-based defect detection algorithms for cracks, chokage, deformation
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to test and validate advanced control strategies in a full-scale operational building. The building will be equipped with a comprehensive sensor network, including access to real-time camera-based occupant
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Electronic Engineering. The Centre is focused on applied research in neuromorphic systems across three pillars: sensors, algorithms, and platforms, and will collaborate closely with its partner ICNS at Western
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analysis; (b) develop and implement algorithms for 3D perception (e.g. segmentation, localization and mapping); (c) design and execute experiments to evaluate, validate and refine algorithms and
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NeuroVision – Neuromorphic Vision Sensor Data Coding. The project focuses on the development of efficient, low-latency, and scalable coding solutions for event-based (neuromorphic) vision sensors, targeting