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25 Jul 2026 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Chemistry Engineering Chemistry Researcher Profile Recognised Researcher (R2) Established
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of computational tools for process monitoring and predictive analysis Candidate Criteria Applicants should have: A PhD in Process Engineering, Chemical Engineering, or a closely related field Strong expertise in
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. Author scientific publications, present findings at conferences, and contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science
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-teaching program, of international level, to meet the research and teaching challenges of UM6P, on green and environmental chemistry applied to all aspects of chemical sciences: organic and inorganic
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precise, customized fertilizer recommendations. Selection criteria (short) Required PhD (awarded or defended before start) in Computer Science, Remote-Sensing/Geoinformatics, Agricultural Data Science, or
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candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically
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Postdoctoral Researcher in Mineral Processing, Battery Materials, and Sustainable Process Engineering. The researcher will join a multidisciplinary research program aimed at optimizing natural graphite for Li
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25 Jul 2026 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Engineering Chemistry Engineering Physics Chemistry Researcher Profile Recognised Researcher (R2
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SUSMAT - Post-Doctoral Fellow Positions in Development of Multifunctional Hydrogels for Agricultural
25 Jul 2026 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Chemistry Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application
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to develop predictive models for polymer-based materials. This project aims to leverage computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials