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Summary: UM6P invites applications for post-doc, in all areas of Computer Systems. A successful post-doc candidate will work with a professor of the College. The position is open to individuals with a PhD
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The Mohammed VI Polytechnic University (UM6P) has an opening for post-doctoral fellow in the field of Environmental Microbial Biotechnology with a strong background in metal stress alleviation and omics
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, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs Summary: UM6P invites applications for post-doc, in all areas of Computer Systems. A
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Description du poste Postdoc / Postdoc description Département / Department : Unité / Unit:Center for African Studies Université / University: Mohammed VI Polytechnic University Durée / Duration
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Host program: College of Agriculture and Environmental Sciences Duration: 2 years (CDD) Description The Mohammed VI Polytechnic University (UM6P) has an opening for post-doctoral fellow in the field
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Discipline: Process Mineralogy, Mineral Processing, Artificial Intelligence Duration: 12 months, with the possibility of renewal for an additional 12 months Institutions: UM6P-Benguerir/ Mineral-X - Stanford University Starting date: As soon as possible We are seeking a Postdoctoral Fellowto...
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Job description : ACER is excited to announce open rank positions for post-doctoral researchers dedicated to advancing the fields of Carbon Negative technology, Capture methods, Utilization
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in Statistial models for optimizing the chemical process Skills in elemental & structural analysis using various existing techniques. Knowledge in advanced structural characterizations will be valued
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of strategic metals and the development of fresh Lithium-ion Batteries & Supercapacitors Experience in Statistial models for optimizing the chemical process Skills in elemental & structural analysis using
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develop independent research activities on the air pollution modelling. Candidate Profile: The Center is looking for a Post-doc to work at the interface between Air Quality modeling and machine learning