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CSAES - Postdoctoral in Experimentation and analysis of the dissolution and diffusion of different fertilizer formulations About UM6P: At the heart of the future Green City of Benguerir
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Job Title: CAES – Postdoctoral researcher in Modeling and quantitative analysis for efficient use and sustainable management of water at the Farm-Scale in semi-arid regions Job Description
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or defended before start) in Computer Science, Remote-Sensing/Geoinformatics, Agricultural Data Science, or related field. Strong track record in remote-sensing imagery and/or time-series analysis and ML/DL
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advanced AI/ML methods for robust analysis and integration. Data sparsity, batch effects, and missing values across different omics layers and platforms. Cross-omics data fusion and representation learning
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. Mathematically, a network is represented by a graph, which is a collection of nodes that are connected to each other by edges. The nodes represent the objects of the network and the edges represent relationships
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collection and analysis systems. Deploy prototypes in the field and optimize their performance based on feedback. Guarantee the reliability, security and scalability of the IoT solutions developed. Work
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publications. Proficiency with statistical analysis and data visualization. Application process: Applications should contain the following documents: Curriculum Vitae A letter (maximum 1 page) explaining
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such as green infrastructure. Utilize digital tools (GIS, hydrological models) to analyze and visualize urban flood risks, droughts, and water flows. Assess the effects of water management strategies
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high-impact journals Contribute to data visualization platforms Required Qualifications Ph.D. in Atmospheric Science, Environmental Science, Remote Sensing, or related field Experience in atmospheric
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. The successful candidate will develop advanced machine learning (ML) models to automate and optimize retrosynthetic analysis, facilitating the discovery of efficient and sustainable synthetic routes for complex