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environments (mining, semi-arid, Saharan). Proficiency in plant functional trait analysis and functional ecology methods. Strong knowledge of soil characterization (physico-chemical analysis, mineralogy, soil
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sequencing (NGS) and omics data analysis. Knowledge of microbial ecology, dysbiosis, and host-microbiome interactions. Familiarity with cell culture techniques. R, Python, or other data science tools
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understanding of the scope and role of organic chemistry in R&D Experience in handling hazardous reagents (solvents, chemicals…) Advanced knowledge in designing and execute experiments, analyze data, and
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and machine learning to optimize treatment conditions. Contribute to the development of reproducible stress priming methods and assist in transferring knowledge to agricultural stakeholders. Required
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Science, Chemical Processes, or a related engineering discipline. A strong background in electrochemical surface science. Proficiency in elemental and structural analysis using various techniques. Knowledge
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Responsibilities: The Postdoctoral Fellows will collaborate with the research team to plan, execute, and analyze research activities and experiments, therefore, contributing to the advancement of knowledge in
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software (e.g., R, SAS, SPSS) and data modeling tools. Knowledge of integrated soil fertility management and sustainable agricultural practices. Publication record: A good track record of publishing research
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of the physical, chemical, and separation properties of membranes. In-depth knowledge of the properties of materials used in membrane manufacturing, including the selection of appropriate materials based
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research, oncology microbiomes, or environmental resistome surveillance. Familiarity with spatial metagenomics, single-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning
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field, and demonstrate a track record of publications in peer-reviewed journals. Exceptional proficiency in English is a prerequisite, and a working knowledge of French is preferred. The successful