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About the recruiter — UM6P Mohammed VI Polytechnic University (UM6P) is a research-and-innovation focused university in Morocco committed to African development. UM6P’s College of Computing (Benguerir & Rabat campuses) advances world-class research and education in Computer Science, fostering...
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of morphing drone prototypes by combining structural optimization, lightweight design, and experimental testing. The research assistant will: Participate in CAD/CAE modeling and structural optimization of UAV
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: Green Tech Institute (GTI) Position Identification Job Title: Logistics Optimization and Environmental Resilience & Sustainability Integration Officer – JORF-Lasfar Entities: GTI-UM6P / SBU Manufacturing
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-driven frameworks for multi-scale modeling, multi-objective optimization, and predictive control of complex chemical and biochemical processes. The research will contribute to next-generation smart
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, the University offers premium conditions for a desirable lifestyle, only 70 km away from Marrakech. Department: Green Tech Institute (GTI) Position Identification Job Title: Logistics Optimization and
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. Process simulation, cost, life cycle, and social assessment of CCUS value chains. Reactor design, optimization, and sizing using phenomenological and/or CFD methods. Energy system analysis. Strong
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, and Sustainable Process Engineering. The researcher will join a multidisciplinary research program aimed at optimizing natural graphite for Li-ion battery applications, developing sustainable
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equipment. You will join an international multidisciplinary team. You will apply simulation, multi-objective optimization, and data-driven analytics to evaluate and compare material intralogistics handling
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team. This position focuses on the development, synthesis, characterization, and optimization of advanced cathode materials for next-generation Lithium-ion batteries. The successful candidate will
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impeller performance, analyze hydrodynamic characteristics, and identify key synthesis parameters influencing material quality. The resulting models will act as a predictive tool for process optimization and