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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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dynamic models. Model complex interactions between physical systems (infrastructure) and digital systems (software, platforms). Develop decision-support tools based on simulations for public and private
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partners, and monitoring budgets. Required Qualifications : PhD: A PhD in digital public health, urban health, data science applied to health or urban planning, smart urban systems, or a related field
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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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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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under investigation. Job Description: The position is open to candidates with a PhD or equivalent in a relevant discipline from a recognized university. Applicants must demonstrate that their doctoral
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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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motivated candidate with a PhD from a recognized University who is passionate about developing innovations that have direct impacts on farmers in arid lands. The candidate will participate in evaluating plant
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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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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