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Field
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orbital sensors (e.g., ECOSTRESS, VIIRS, Landsat/MODIS) to build pre- and post-fire structural and functional diagnostics. Develop recovery chronosequences from multi-sensor time series and quantify
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particular focus on applications relevant to the Arab world. The successful applicant will join a multidisciplinary research team working at the intersection of machine learning, algorithmic fairness, human
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conferences and journals. Overview: The successful candidate will join an interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific
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The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL). Northwestern, TTIC, and UIC. Position ID: Northwestern-The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL
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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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AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making algorithms for process industries (e.g., chemical, pharmaceutical, materials
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project that involves designing microfabricated biomedical sensors and the readout circuitry for recording electrophysiology and electrochemical signals from biological samples. The overarching goal
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different research areas. The more details can be kindly found as below: 1. Industrial AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making
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developing novel methods and algorithms for applications in the Engineering Design domain; demonstrating a commitment to deliver results; working on research proposals; and working in a team environment. Job
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central controller). ● Develop and validate calibration methods for new sensors for turbidity and existing commercial sensors. ● Explore high-frequency turbidity monitoring as a tool for assessing