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, campus environment. This MAS will leverage cutting-edge autonomy algorithms and stacks developed at UMD and employ 5G networks for command and control. This project is funded by an entrepreneurial donor
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in the National Academy of Engineering, fellowships in professional scientific organizations including ACM and IEEE, NSF Faculty Early Career Development awards and Sloan Fellowships. It is home to
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validating science algorithms, post-flight calibration and validation, developing field observation databases, science data product development and the fusion of multi-sensor data. There is also the
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Qualifications: Education: BS in Geospatial Data Science, Geographic Information Science, Computer Science or close equivalent. Experience: Experience developing and optimizing algorithms. Extensive programming
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Professor rank) in one of the Smith School’s strategic focus areas including: Artificial intelligence (AI) applications in operations management and business analytics; algorithmic bias and responsible AI