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skills in machine learning, deep learning, and advanced statistics for processing complex data. Urban Health Principles: Familiarity with urban planning principles centered on health (active mobility
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at conferences, and stakeholder engagement sessions. Required Qualifications: A Ph.D. in Climate Science, Hydrology, Environmental Science, or a related field. Experience in machine learning or AI applications in
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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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modelling. Candidate Profile: The Center is looking for a Post-doc to work at the interface between Air Quality modeling and machine learning to evaluate air pollution in Morocco and Africa using modelling
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Research, Variational Methods, Probability, Stochastic Processes, Complex Systems, Network Science, Linear Algebra, Data-Driven Modeling, Scientific Machine Learning, Numerical Analysis, Computational
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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
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on the development of new easy, accurate, and low-cost tools for soil agricultural soils diagnosis based on the coupling of spectroscopic techniques (FTIR, NIR, Raman, …) with machine learning/ chemometrics