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. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing multidimensional networks by studying the theoretical foundations behind randomized
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. The candidate will need to master sensor technologies, embedded systems, and communication protocols, while integrating real-time data into cloud platforms to develop reliable, secure, and scalable solutions
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of precipitation and temperature over Morocco. Key Responsibilities: Statistical model development: Led the development of advanced statistical models and machine learning algorithms for forecasting precipitation
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to join our cutting-edge team, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be
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environmental sensors and thermal cameras (UAV/IR). Comparative analysis of PV configurations: with vs. without vegetation. Studying dust deposition and its impact on energy performance. Analyzing meteorological
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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