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Qualifications PhD in Microbiology, Immunology, Systems Biology, Bioinformatics, or a related discipline. Proven experience in microbiome research, particularly in gut microbiota. Experience with next-generation
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communications. The candidate must hold (or about to complete) a PhD in the related fields. The candidate will be involved in a two-year research project in collaboration with international academic partners
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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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website at https://agc.um6p.ma for further details. The ideal candidate must possess a PhD degree in Microbiology, Molecular Biology, Microbial Genomics, Bioinformatics, or an equivalent field. They should
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selected in accordance with this and expected to be in the upper segment of its class with respect to academic credentials. Candidate must hold a PhD in synthetic organic chemistry and must have: Clear
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evaluations carried out in the presence of crops. Required qualifications: The candidates must have strong experience in MOF synthesis and characterization with a PhD and demonstrated experience in Materials
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to grant writing and development of new research proposals. Required Qualifications: PhD in Microbial Genomics, Bioinformatics, Molecular Microbiology, Infectious Disease Biology, or a related field. Proven
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Qualifications PhD in Microbiology, Immunology, Systems Biology, Bioinformatics, or a related discipline. Proven experience in microbiome research, particularly in gut microbiota. Experience with next-generation
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from a recognized university. The candidate should demonstrate that their PhD work and past experience allow them to have a connection to one or several aspects of the areas of research mentioned above
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. Ensure timely delivery of project milestones and deliverables. Mentorship and training: Supervise and mentor PhD students and research assistants involved in the project. Provide training on experimental