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Field
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quantum sensing technologies (e.g., Rydberg atomic sensors) for wireless communications and sensing. Key Responsibilities: Develop quantum-related theories, models, and algorithms for various communications
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analysis for more geometries and with a reduced number of sensors - Implementation of the MSE method on a cylindrical structure immersed in water and sensitivity analysis - Algorithmic and experimental
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, focusing on intelligent sensor tasking and the automated identification and characterization of space objects in Earth orbits and cislunar environment using optical data. Contribute to the development
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for SDA, focusing on intelligent sensor tasking and the automated identification and characterization of space objects in Earth orbits and cislunar environment using optical data. Contribute
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Language Processing (NLP). We seek outstanding candidates with expertise in developing and applying AI techniques that integrate and reason over multiple modalities—including text, speech, vision, and sensor data
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are searching for motivated and talented Signal Processing Research and Development Engineers to join our Sensor Analysis and Data Modeling (SADM) Department at the Applied Research Laboratory (ARL) at Penn State
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the development of image/signal processing algorithms from a multidisciplinary approach, to include multiple sensor modalities. These multidisciplinary research opportunities incorporate theoretical and
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sensors and DAS, acquired at sampling rates ranging from 1,000 to 200,000 samples per second, is capable of observing magnitude negative five induced earthquakes at distances from meters to 100’s of meters
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations