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, sorting, recycling, recovery, and disposal processes and infrastructures. Specific Waste Streams: Knowledge of specific waste streams (organic, electronic, hazardous, etc.). IoT Technologies: Experience
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(e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference, causal
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
, PyTorch, Scikit-learn). Knowledge of metabolomics data analysis, including LC-MS, NMR data preprocessing, normalization, and feature extraction. Familiarity with multi-omics data integration, biomarker
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separation and magnetic phenomena, as well as expertise in experimental methods to study the interactions between magnetic fields and solid and liquid materials. Additionally, knowledge of the physical and
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ameliorants to enhance carbon sequestration and arrest soil erosion by wind. The candidate is expected to roll out multilocation trials and laboratory scale experiments and develop knowledge that can contribute
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the tasks according to the service needs. Knowledge of Arabic, French and English is sufficient to support teaching activities for students and farmers as well. Analytical skills related to site budget
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Ability to initiate, conduct, and publish research in a scientific manner and to obtain external grant funding Well-developed oral and written communication skills Desirable: Working knowledge of statistics
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-time PCR, and Flow cytometry. Advanced Knowledge in skin biology and technical skills in cosmetic formulation. Proficiency in the use of software and databases and statistical analysis. Publish in well
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strong record of scientific publications. Ability to work independently as well as collaboratively in a multidisciplinary team. Knowledge of molecular biology techniques, microbial cultivation, and soil
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). Knowledge of environmental sustainability, soil health, or plant-microbe interactions. Proficiency in the use of bioinformatics tools for metagenomic and transcriptomic data analysis (e.g., QIIME, DADA2, R