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, data science applied to health or urban planning, smart urban systems, or a related field. Expertise in Big Data Analysis: Proven expertise in analyzing and processing large urban datasets for public
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processes. We work diligently to contribute to the competitiveness of Moroccan and African companies by conducting research across a wide range of applied sciences. Our main activities turn around key pillars
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professionals in order to boost its quality-oriented research environment in the metropolitan area of Marrakech. ABOUT MSN DEPARTMENT: The Materials Science, Energy, and nano-engineering (MSN) is a department at
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Institution: Mohammed VI Polytechnic University (UM6P) Department: Chemical and Biochemical Sciences - Green Process Engineering (CBS) Location: Benguerir/Jorf Lasfar, Morocco Duration: 12 months
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, including the analysis of public policies, stakeholder dynamics, and urban strategies. Interdisciplinary Collaboration: Work closely with experts in political science, urban planning, urban sociology, and
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Qualifications Ph.D. in hydrology, environmental engineering, urban planning, or a related field. Expertise in urban hydrology, water cycles, and stormwater management. Strong background in flood and drought risk
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, mainly IWRI and CRSA, as well as institutions and stakeholders to translate research findings into actionable water management strategies. Qualifications: Ph.D. in Hydrology, Environmental Science, Earth
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Institution Overview: Mohammed VI Polytechnic University is a leading institution dedicated to research and innovation in Africa. Committed to fostering economic and human development, the University places research and innovation at the forefront of progress. Located in Benguerir, at the heart...
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Postdoctoral Researcher in Geological Exploration of Carbonatite Complexes and Associated Critical Minerals Geology & Sustainable Mining Institute Mohammed VI Polytechnic University - Benguerir - Morocco Job Description The Geology and Sustainable Mining Institute (GSMI) of University Mohammed...
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. Contribute to the supervision of master and PhD students. Qualifications: Ph.D. in Earth Sciences, Remote Sensing, Physics, Applied mathematics, or related field. Strong background in land surface modeling