43 industrial-management Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY in Morocco
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: Ability to write technical reports and scientific publications. Experience collaborating with multidisciplinary academic and industrial teams. Project management and team supervision capabilities. Candidate
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to an entrepreneurial ecosystem directly related to its industrial and socio-economic environment in Morocco and Africa. HTMR provides highly automated and parallel approaches to the development of new materials and
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&D center of UM6P that focuses on developing new technologies and scaling them up to bridge the gap between academia and industry. It serves national and international clients and is collaborating with
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levers to reduce costs and lead times. Develop strategies and risk management models to enhance the system’s resilience against logistical disruptions. Implement energy management approaches and CO
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Responsibilities: Design, synthesize, and characterize microporous materials (e.g., porous ceramics) tailored for agricultural applications. Investigate the interaction of microporous materials with soil and plant
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scientific papers to study the botany and ecology of native desert plant species of south of Morocco as well as their interaction of their ecosystems including the soil. The successful candidate will conduct
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characterization of metal-organic frameworks (MOFs) and their composites using sustainable alternatives, such as waste and industrial by-products. The synthesized materials will subsequently be applied in catalysis
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in industrial waste Decarbonization in smart building ACER is engaged in pioneering research and development projects to promote innovation in industrial decarbonization pathways. The open rank
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Title: ASARI - Postdoctoral Position in Management and valorization of wastes and residues from mining and industrial sites Entity: ASARI About UM6P: Mohammed VI Polytechnic University (UM6P) is an
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real-world applications in green chemistry and industrial synthesis. Key Responsibilities: Develop and implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic