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providing guidance to PhD students who are actively involved in ecohydrological modeling research. Conduct laboratory analyses and field work. Collaborate with local researcher from the college of agriculture
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and providing guidance to PhD students who are actively involved in ecohydrological modeling research. - Conduct laboratory analyses and field work. - Collaborate with local researcher from the college
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system for bacterial genomes using cutting-edge genomic language models. This project aims to adapt and extend transformer-based architectures to create a powerful tool for understanding and predicting
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: Mathematical Modeling: Develop mathematical models to simulate and optimize the entire waste management chain—from collection to treatment. Data Integration and Analysis: Integrate real-time and historical data
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of the candidate: PhD in atmospheric sciences or a closely related field The candidate should have experience in climate model development and assessements A strong programming background and use of HPC are required
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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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funding applications Selection Criteria and Skills of the Candidate: Completed a PhD in engineering, applied physics, applied mathematics, or a related field. Strong quantitative skills and modeling
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computer programming tools such as Matlab and/or Python. Knowledge of statistics and mathematical modeling. Experience in large spatial data processing, analysis, and interpretation. Experience in running
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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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tools, data science techniques, and spatial analysis to leverage big data from cities and model their evolution. Main Tasks and Responsibilities: Collect, clean, and structure large volumes of urban