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to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data assimilation, machine learning, and seasonal weather forecasts. As a
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. The successful candidate will answer questions such as how to assign limited communication resources to train the federated machine learning model efficiently. She/he will investigate realistic scenarios including
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multidisciplinary team. Ability to write publications, reports, and projects. Oral and written communication skills. Computer skills/programming/modeling would be a plus. Candidate Criteria Ph.D. in Chemical
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oriented institution of higher learning committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development of Morocco and
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communication resources to train the federated machine learning model efficiently. She/he will investigate realistic scenarios including non-iidness of data distribution, system heterogeneity, and dynamic
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and machine learning to optimize treatment conditions. Contribute to the development of reproducible stress priming methods and assist in transferring knowledge to agricultural stakeholders. Required