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, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs Summary: UM6P invites applications for post-doc, in all areas of Computer Systems. A
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of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions. 2. Key Responsibilities
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infrastructure, mobility, and energy management. Integrate real-time data from sensors and IoT devices to develop dynamic models. Model complex interactions between physical systems (infrastructure) and digital
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). Nutritional monitoring of boron in Eucalyptus spp. in the Brazilian cerrado by multispectral bands of the MSI sensor (Sentinel-2). Remote Sensing Applications: Society and Environment, 29, 100913. Roux, P
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sensor data, public databases, and GIS. Predictive Modeling:Design predictive models to evaluate the impact of urban and environmental policies on public health. Interdisciplinary Collaboration:Collaborate
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with IoT technologies (smart sensors, connected devices) for real-time monitoring of waste systems. Circular Economy: Familiarity with circular economy principles as applied to waste management
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the metropolitan area of Marrakech. The College of Computing at Mohammed VI Polytechnic University (UM6P), Benguerir, Morocco, seeks a postdoctoral candidate in wireless sensor networks and the Internet of Things
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. Proficiency in programming MATLAB and Python for data analysis and algorithm development. Knowledge of data assimilation techniques is a valuable added. Excellent communication skills and ability to work
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). Nutritional monitoring of boron in Eucalyptus spp. in the Brazilian cerrado by multispectral bands of the MSI sensor (Sentinel-2). Remote Sensing Applications: Society and Environment, 29, 100913. Roux, P
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precipitation, temperature, and soil moisture by leveraging large multi-source datasets from remote sensing, IoT sensors, and climate models. Design and implement deep learning models for forecasting extreme