88 linked-data-"https:"-"https:"-"https:"-"UCL" Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY
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of diversity and equal treatment issues with a particular focus on gender equality Analyse experimental data, interpret results, and contribute to the development of new hypotheses and research directions
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team to write scientific reports, prepare research publications, and effectively communicate results and data analysis in both French and English. Candidate Criteria Ph.D. in Chemistry, Organic Chemistry
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analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission management platforms, contributing to the deployment of smart UAV demonstrators under
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The School of Computer and Communication Sciences at Mohammed VI Polytechnic University (UM6P), Benguerir, Morocco is currently looking for motivated and talented Postdoctoral researchers in
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. Oriented towards Africa, ASARI acts in connection with a wide network of universities and research centers around the continent in order to link real field issues with up-to-date science. The institute has
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must demonstrate a strong understanding of sedimentary basins, excellent proficiency in analyzing the different facets of hydrocarbon reservoir systems, interpreting seismic data, and applying structural
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background in trace element dynamics, soil–plant interactions, or environmental biogeochemistry. Experience in experimental design, data analysis, and scientific writing Added value: expertise in microbial
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methods, instruments and perform data acquisition related to the project. Write proposals, reports, scientific articles and Patent proposals related to the project. Candidate Profile Strong proficiency in
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link real field issues with up-to-date science. The institute consists of a multidisciplinary team of agronomists, biochemists, molecular biologists, bioprocess specialists, animal scientist, etc
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
-dimensionality and complexity of metabolomics data, requiring advanced AI/ML techniques for robust analysis and interpretation. Integration of multi-omics data (genomics, transcriptomics, proteomics, and