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, reports and projects. Oral and written communication skills. Computer skills/programming/modeling would be a plus. Candidate Criteria Ph.D. in Analytical Chemistry or a related field. Extensive experience
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Responsibilities: Develop and improve emission inventories for Morocco. Perform source apportionment analysis using statistical and computational techniques (e.g., receptor models, chemical transport models
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of Applied and Engineering Physics is a premier engineering physics school in Morocco. Over a rigorous three-year program, it prepares physicists to become future entrepreneurs, leaders, and professionals
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, distributed ones. Their low input data requirements and flexible application make them widely used by water managers. While very attractive, these models can be pretty challenging when attempting to compute
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combined with modeling experiments or enhanced research in parameterization, AI is accelerating computational processes, improving prediction accuracy, and enabling the creation of extensive model ensembles
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Global Critical Zone Science Chair to develop and conduct a research program to better understand forest nutrition and nutritional stress in Eucalyptus forest stands in Brazil. Research context: Forests
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characteristics, and flight dynamics. Develop and enhance computational fluid dynamics (CFD) models, wind tunnel testing techniques, and aerodynamic analysis and optimization simulation tools. Investigate aircraft
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in programming (Python, Julia) (provide evidence with specific examples). Experience with statistical modelling and experimental design. Ability to work in a multidisciplinary team. Strong written and
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efficiency, ion separation rates, energy consumption, etc. Model ion transport and system behavior under different operational conditions. Collaborate with researchers in diverse projects and contribute
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computational tools and simulation software for modeling chemical equilibria and mass transfer processes A commitment to pedagogical innovation and the ability to mentor and engage students in active learning