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sustainability. The selected researcher will contribute to the development of predictive models and machine learning algorithms for data analysis from plant-based sensors, multispectral and thermal imagery, and
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next-generation multiphysics tomography sensors for real-time monitoring of industrial flows. By embedding AI directly into sensing hardware, fluiidd enables industries to “see” inside opaque systems and
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measurements Calibration of materials as sensors to measure temperature, oxygen, and pH values in cells Development of models based on artificial intelligence algorithms to interpret luminescence signals Study
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models using experimental data from drivetrain test benches equipped with load, temperature, vibration, and acoustic sensors. Integrating the models into a Model-Based Systems Engineering (MBSE) framework
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us. II. Positions and Requirements Position 1: Scientist in Intelligent Biobreeding Algorithm Responsibilities: Lead the formation and direction of an interdisciplinary team to integrate AI
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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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-on experience building or modifying equipment and working effectively within multidisciplinary teams. Experience with Linux, ROS/ROS2, electronics and sensor integration, algorithm design, and laboratory
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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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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
focused on environmental 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