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and Space Weather. The successful candidate will contribute to the development, testing, and operation of solar monitoring stations, real-time data pipelines, and AI-based analysis tools. The position
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of this annex, as well as to: Programming in Python and R. Statistical classification and machine learning methods: SVM, neural networks and logistic regression. 3.2. Qualification: Official Master’s degree in
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» Electrical engineering Engineering » Other Researcher Profile First Stage Researcher (R1) Country Estonia Application Deadline 26 Oct 2025 - 21:59 (UTC) Type of Contract Temporary Job Status Full-time Hours
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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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on the monitoring and response parts, building on many earlier projects revolving around the use of UAV/drones, computer vision and machine learning, change and damage detection, and multi-data integration, such as
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degree. Required qualifications (documentation required) Academic background as listed above Training in machine learning Very good English skills (written and oral) Very good computer programming skills
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these sounds fascinating, then this PhD position is made for you! Information We invite highly motivated students with a strong background in mathematical control theory, and a keen interest in machine learning
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driving, in-car monitoring, industrial automation, and security surveillance. The research, called "R4DAR," aims to leverage emerging 4D imaging technology with Massive MIMO to create image-like radar
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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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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 1 month ago
, « A review of ultrasonic sensing and machine learning methods to monitor industrial processes », Ultrasonics, vol. 124, p. 106776, août 2022, doi: 10.1016/j.ultras.2022.106776. - T. Ageyeva, S. Horváth