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areas that aim to ensure the challenging Food and Water security goal in Africa, with a special focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve
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. Research within CRSA is organized around several major areas that aim to ensure the challenging Food and Water security goal in Africa, with a special focus on developing methods/tools that use multi-source
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interfaces, and condensation surfaces under varied operating scenarios. Develop and refine performance simulation models and predictive tools to support system optimization and deployment strategies. Prepare
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design simulation studies using water, soil and crop modeling tools Compile and analyze experimental data, interpret results, prepare presentations and manuscripts, and publish in high-quality peer
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IoT-oriented databases (e.g., InfluxDB, PostgreSQL, Firebase, etc.). Knowledge of data visualization tools (e.g., Grafana, Tableau, etc.). Personal and organizational skills Ability to solve complex
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tools such as R packages, Phyton, and other programming languages Publications in the field Excellent communication and interpersonal skills. High motivation and interest in scientific work Applications
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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
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physicochemical and analytical tools such as spectroscopy, microscopy, porosity analysis, to assess structure-property relationships. Conduct comprehensive evaluations of developed fertilizer formulas in laboratory
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responses. Experience with high-throughput phenotyping tools and data analysis. Publication record demonstrating expertise in phenotyping, image analysis, or related fields. High publication record; books
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software and techniques. Background in plant biology and physiology, especially related to stress responses. Experience with high-throughput phenotyping tools and data analysis. Publication record