27 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at MOHAMMED VI POLYTECHNIC UNIVERSITY
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21 Aug 2025 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Biological sciences Computer science Researcher Profile Recognised Researcher (R2) Established
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) Country Morocco Application Deadline 1 Oct 2025 - 00:00 (UTC) Type of Contract To be defined Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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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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disciplines and create an environment for interdisciplinary research. The research program of ACER is multidisciplinary, with faculty members from backgrounds in Chemistry, Chemical Engineering, 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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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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on performance requirements is required. The postdoctoral fellow will join the CBS-IGSAC department where he will be responsible for participating in the conduct of a research program on the valorization
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results and contribute to the writing of scientific articles. Candidate Profile: PhD in plant ecology, soil science, environmental science, or a related discipline. Proven experience in arid or degraded
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conclusions. Student Supervision: Play an active role in mentoring and supervising both graduate (MSc and PhD) and undergraduate students, fostering their academic and research growth. Teaching Contribution
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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