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Field
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Exploration - Source localization 2. Perception in sensor-degraded environments: - Localization in smoke and dust filled environments - Scene awareness - Biometric/triage evaluations, etc. 3. Mission-specific
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and image data processing. Specific knowledge related to neural network design, training, and optimization is required. You will be joining a group with core expertise in sensor data analytics from
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-based Exploration - Source localization 2. Perception in sensor-degraded environments: - Localization in smoke and dust filled environments - Scene awareness - Biometric/triage evaluations, etc. 3
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of sensors and devices on novel substrate materials, and develop novel active materials and fabrication methods to integrate all functionalities into these substrates create a database for passports and life
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systems using cost effective sensors and IoT devices. To enhance assessment reliability, full-scale measurements will be conducted. The results will be analysed to identify the cause of the disturbance
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of a sustainable industry. At the same time, complexity is increasing through digital decision support systems, sensors, AI, and augmented reality. The goal is to develop knowledge and concrete design
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Multimodal human-centric understanding and adaptation Active sensor fusion for increased robustness and adaptivity In addition, the duties of the doctoral researchers may include some teaching tasks (5-10%) in
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- Markovian Processes - Network Based Localisation / Radio based connectivity - Adaptive bandwidth - Mesh networking - Wireless Sensor Networks - Edge Computing - Time Delayed Systems - Adaptive Queuing
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releases, and greenhouse gas flux estimation. Current approaches struggle to assimilate data from heterogeneous sensor networks, are too computationally demanding for real-time deployment, and lack reliable
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METATUNE-MSCA-DN – DC15_Multispectral metalenses for 3D imaging_Photonic Sensors and Algorithms SL_Spain..pdf English (139.17 KB - PDF) Download Additional Information Website for additional job details