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Polytechnic University (UM6P), Benguerir, Morocco, is seeking for a postdoctoral candidate in the area of machine learning for IoT networks. The candidate must hold (or about to complete) a PhD in the related
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Intelligence Climate Change Urban and Territorial Sustainability Water–Energy–Food Nexus Position Description African Research Center on Air Quality and Climate (ARC_AIR) of UM6P invites applications for a
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within UM6P. The position is open to individuals who hold a Doctoral degree in the subject discipline from a recognized university. The candidate should demonstrate that their PhD work and past experience
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purification, sensing and/or waste transformation/energy efficiency. Other duties include advising graduate students and contribution to build up a first-class research-oriented research program at UM6P
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professionals in order to boost its quality-oriented research environment in the metropolitan area of Marrakech. ABOUT MSN DEPARTMENT The Materials Science, Energy, and nano-engineering (MSN) is a department at
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multidisciplinary, with faculty members from backgrounds in Chemistry, Chemical Engineering, and Environmental Engineering focusing on different research fields such as catalysis, separation, energy generation
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research clusters including Energy Transition, Surface Technology and Metallurgy, Polymers and Composites, and Sustainable Materials. With some 100 researchers and PhD students and several national and
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for industrial implementation and Water-Energy-Materials nexus. Collaborate with suppliers, support staff, and other engineers, PhD students to plan and implement experiments related to the project. Set up testing
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on multiple cell lines Perform experiments to study cell behavior under different conditions Conduct multiparametric flow cytometry analyses for cytotoxicity and functional cellular assessment Develop new
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candidate is expected to: Design and perform advanced cell culture experiments on multiple cell lines Perform experiments to study cell behavior under different conditions Conduct multiparametric flow