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candidate in the area of machine learning for IoT networks. The candidate must hold (or about to complete) a PhD in the related fields shown below. The candidate is expected to have hands-on experience in
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communication resources to train the federated machine learning model efficiently. She/he will investigate realistic scenarios including non-iidness of data distribution, system heterogeneity, and dynamic
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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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fieldwork, including floristic surveys, soil sampling, and ecological data collection. Conduct advanced analyses of plant functional traits and their phytoremediation potential. Contribute
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Yield Forecasting". This project aims to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data assimilation, machine learning
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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
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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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metabolism Key Responsibilities Lead metagenomic, proteomics, and metabolomic profiling of clinical and experimental samples to identify dysbiosis signatures. Apply bioinformatics tools for microbiome data
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, Professor Venturi’s research program extends to unraveling the intricacies of bacterial cell-cell signaling within plant microbiomes. As a postdoc, you will delve into genomics and metagenomics data
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We are in search of a highly qualified researcher for one postdoctoral research opening in our team. Please see the information below: Postdoctoral Fellowship in Organic Chemistry Duration: 12