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of machine learning. develop novel machine learning algorithms primarily for representation learning, dimensionality reduction, clustering and search. conduct theoretical and experimental performance analyses
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. Develop and fine-tune LLMs to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain experts to integrate LLM-based
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patterns may mimic those observed in irrigated croplands. Key Responsibilities: Conduct research to develop algorithms and methodologies for mapping irrigation patterns using satellite imagery. Investigate
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to develop algorithms and methodologies for mapping irrigation patterns using satellite imagery. Investigate methods for detecting the timing and frequency of irrigation events from time-series remote sensing
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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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algorithms in various projects. Contribute to the supervision of doctoral students and interns at the center. Participate in the training courses organized by the center. Work on collaborative projects with
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to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain experts to integrate LLM-based solutions into predictive
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data for model calibration and validation. Apply sensitivity analysis and optimization algorithms to refine model parameters and improve predictive accuracy. Contribute to code development, documentation
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, the next step in this project is to address sparse optimization for tensors. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing
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) to predictive maintenance challenges. Develop and fine-tune LLMs to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain