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, and labor shortages. Currently, most animal monitoring and inspections are performed visually by humans, which is time-consuming and error-prone. Computer vision, leveraging recent advances in deep
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engineering, electrical engineering, data science, or a related field. Skills in embedded systems development, electronics, or IoT (C/C++, Python, Arduino/ESP32, etc.) OR in machine learning and sensor data
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Martin Australia invite applications for a project under this program, advancing robotic perception systems through monitoring of their machine learning models. Run-Time Monitoring of Machine Learning
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, Cascais, Riga, Vilnius, Melsungen, Ciampino, Urla and Rhodes. The PhD project will involve: The use of data analytics (statistical models, machine learning, uncertainty quantification) to monitor and
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monitoring and health monitoring of the different machine components. To this end, multiple dedicated measurement campaigns have been performed throughout the Belgian offshore zone, resulting in a large in
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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/Administrative Internal Number: 527353 Pay Grade/Pay Range: Minimum: $62,300 - Midpoint: $81,000 (Salaried E10) Department/Organization: 214251 - Electrical and Computer Eng Normal Work Schedule: Monday - Friday
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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smart monitoring methods can be used to investigate the ecological status of smaller -often unmonitored- water bodies. These water bodies make up one-third of the total number of water bodies in