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independent and collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation
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independent and collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation
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independent and collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation
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interests and expertise: IoT research and development, including sensor integration and communication improvement. Mechanism research and algorithm development for real-time monitoring and early warning to
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focuses on algorithm development, data fusion, and deployment for anomaly detection in solar panels and battery systems. Key Responsibilities Develop computer vision and deep learning algorithms
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embedded FPGA-based intelligence near seismic sensor arrays, you will explore methods to maximize prediction performance while minimizing data transmission and latency. Your key tasks include: Evaluating
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feeds Development of a sensor platform for multimodal Camera/RADAR perception assisted by AI H/F 169 / 815 vacancy Vacancy details Position description Category Mathematics, information, scientific
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, among others. Non-UW In addition to coordinating activities with CICOES personnel both for fieldwork deployment and algorithm development, the Software Engineer will coordinate with external entities in
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develop science-driven analyses that help inform future sensor requirements. The position also provides opportunities to investigate how modern artificial intelligence and scientific machine learning
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vehicle and sensor systems, developing standardized test procedures, and applying AI to scenario generation and system evaluation. The ideal candidate will have a strong background in vehicle systems