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Modeling and Crop Yield Prediction in Africa Area of specialization: Agronomy, Modeling, biostatistics, Job/Project description: The AgroBioSciences Program (AgBS) at the Mohammed VI Polytechnic University
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visiting scholars worldwide, the Centre is committed to training a new generation of African Atmospheric Scientists and faculty members. Research endeavors primarily focus on experimental and Modelling
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time, the main tools for providing such information for planning purposes have been hydrological models. They come in various configurations, from simple, conceptual lumped models to more complex
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Africa. The successful candidate will use advanced land surface modeling calibrated to observations from field trails and satellites to assess implications for crop yields and carbon sequestration under
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methods for detecting the timing and frequency of irrigation events from time-series remote sensing data. Develop models and techniques to quantify water supply and irrigation efficiency in agricultural
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data. Develop models and techniques to quantify water supply and irrigation efficiency in agricultural landscapes. Collaborate with multidisciplinary teams to integrate remote sensing data with ground
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candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage
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of morphing drone prototypes by combining structural optimization, lightweight design, and experimental testing. The research assistant will: Participate in CAD/CAE modeling and structural optimization of UAV
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interpretation of remote sensing data, allowing for rapid decision-making in critical situations, such as during natural disasters. AI models can process big datasets efficiently, helping to make informed
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embeddings, contrastive learning, or foundation models. Solid background in linear algebra, probability, and statistics. Strong programming skills with deep learning frameworks (e.g., PyTorch) and standard