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Field
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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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sensor research and development for energy applications, with a focus on advanced manufacturing technologies. The MSA group consists of staff members with backgrounds in mechanical engineering, materials
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, encryption/decryption and compression; use of microelectronics devices (including COTS); implementation, inference, verification and validation of algorithms** on processing hardware platforms for space
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novel ideas on searches for dark matter and other physics beyond the Standard Model with quantum sensors, including development of quantum algorithms for atomic clocks and other quantum sensors
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-criteria, defining their formalization as fuzzy subsets, and characterizing their uncertainty; Integrating Machine Learning algorithms to better account for low-level sensor data (precipitation, wind-driven
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satellite datasets and employ near-real-time server-side algorithms for time-series analysis and the generation of value-added geospatial maps. To enhance the sustainability performance and competitiveness
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closely with a small, dedicated team, you will: Design and implement SLAM-based navigation algorithms for GPS-denied forest environments (45%) Develop multi-sensor integration software for LiDAR, cameras
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(AIED) and Educational Data Mining (EDM) projects with Professor Kalina Yacef. These projects explore how multimodal data from online platforms and sensor-based environments can be harnessed to enhance
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satellite sensors, customized to taxa and water quality typical of the U.S. West Coast. Apply data from ocean color and/or land imaging satellite missions as appropriate (e.g. PACE, Sentinel 3, MODIS