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monitoring and electric vehicle battery tracking. Integrate environmental and energy sensors with real-time data collection and analysis systems. Deploy prototypes in the field and optimize their performance
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foundation in Bio/chemistry, Bioprocess, and Microbial Biotechnology. Additionally, candidates should possess expertise in molecular biology and chemical analysis. Proficiency in biostatistical analysis, data
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Green Process Engineering Department (CBS) is a component of the Mohammed VI Polytechnic University (UM6P). The main objective of CBS is to set up a distinctive research-teaching program, of international
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devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence for predictive and prescriptive urban data analysis. Experience in visualizing and analyzing spatial
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such as spatial justice, socio-spatial segregation, territorial divides, and inclusive development. Proficiency in spatial analysis to examine inequality dynamics at various scales (urban, rural, regional
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assessment in urban environments. Proficiency in hydrological modeling software (SWMM, HEC-RAS, or equivalent). Experience with GIS tools (ArcGIS, QGIS) for spatial analysis and mapping of water flows and risk
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: Mathematical Modeling: Develop mathematical models to simulate and optimize the entire waste management chain—from collection to treatment. Data Integration and Analysis: Integrate real-time and historical data
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their economic significance. Key Responsibilities Conduct geological fieldwork, including mapping, sampling, and structural analysis of carbonatite complexes and associated rocks and minerals; Monitoring
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experience in natural product extraction, purification, and metabolite identification. Proficiency in the use of LC-MS/MS, GC-MS/MS, NMR, and relevant data analysis software (e.g., MestReNova, Thermo
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: A PhD in extractive metallurgy or related subject. Expert in metal extraction, heat treatment & refining processes. Expert in chemical characterization of valuable metals and/or alloys. Excellent