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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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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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feeds Development of a sensor platform for multimodal Camera/RADAR perception assisted by AI H/F 110 / 795 vacancy Vacancy details Position description Category Mathematics, information, scientific
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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
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, and distributed decision-making. • Design and implement software solutions in Python and/or C++, including algorithm development, optimization, and deployment on embedded computing
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Job Posting Title: Assured PNT and Sensor Fusion Research Associate ---- Hiring Department: Applied Research Laboratories ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40
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external forces and torsional response can instead be estimated using methods such as convex optimization or Kalman filtering. These torque estimation methods allow much more freedom in sensor