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Machine Learning models for quality prediction and control of phosphate ore. Simulating and evaluating various extraction scenarios, considering industrial constraints. Collaborating closely with field and
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material-system interactions, particularly the performance of adsorbents, thermal interfaces, and condensation surfaces under varied operating scenarios. Develop and refine performance simulation models and
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model improvements in simulating Moroccan and North African climate. Carry out evaluation of the model outputs and prospect possible changes to improve water cycle modeling, including precipitation
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productivity. The platform includes: An outdoor system with a (i) a fully automated lysimetric system with 1400 large container (mini-plots) to study water dynamics and drought scenarios simulation under
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their thermophysical properties. Proficiency in computational fluid dynamics (CFD) simulation of thermal energy storage systems, enabling the modeling and analysis of heat transfer, fluid flow, and thermodynamic
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health. Predictive Modeling Skills: Ability to develop predictive models and simulation tools to assess the impact of urban interventions on health. Smart City Experience: Experience in developing smart
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materials relevant to thermal energy storage, including conducting structural characterizations and studying their thermophysical properties. Proficiency in computational fluid dynamics (CFD) simulation
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing
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initiative and undertake outreach, including publication of research findings Prepare and design simulation studies using water, soil and crop modeling tools Compile and analyze experimental data, interpret
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, simulation and optimization of the phosphate value chain processes. In terms of research, the candidate will reinforce the team of the CBS department. His/her experience and expertise should enable him/her