13 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"CESBIO"-"CESBIO" Fellowship positions at MOHAMMED VI POLYTECHNIC UNIVERSITY
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security goal in Africa, with a special focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning
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, Plant Science, Environmental Science, or a related field. Expertise in microbiome data analysis, metagenomics, or metaproteomics. Proficiency in bioinformatics tools for multi-omics data processing Strong
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: Present a table listing your indexed publications, arranged in descending order from the most recent to the oldest. Include information about your authorship position (e.g., First position) and provide
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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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sciences, or a closely related field. Proven experience in omics data generation and analysis (transcriptomics, proteomics, metabolomics). Strong background in microbial physiology, protein/peptide
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–soil interactions, droughts, and desertification Water-related hazards and risk assessment Climate change impacts and adaptation strategies Integrated Coastal Zone Management (ICZM) Water information
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discovery and innovation. The College currently offers an engineering degree in computer engineering, and a doctoral program in computer science. About the Group The Data Intelligence Group at UM6P-CC is a
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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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environmentally friendly alternatives. Funding information: This position is available for one year, extended to two years depending on the performance. Interested applicants should submit their online application
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metabolism. Key Responsibilities Lead metagenomic, proteomics, and metabolomic profiling of clinical and experimental samples to identify dysbiosis signatures. Apply bioinformatics tools for microbiome data