117 software-defined-networking Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY in Morocco
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-to-date science and technology. 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
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bioenergy, cultivation and conversion of micro and macroalgae, and geology and mining. Oriented towards Africa, ASARI acts in connection with a wide network of universities and research centers around the
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at Benguerir (50 km north of Marrakech), Morocco. The net salary per month is 2000 USD. The initial appointment as Postdoctoral researcher will be for one-year renewable depending on satisfactory performance
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Qualification Type: Postdoctoral position Location: Ben Guérir, Morocco Funding for: National/International Researchers Funding amount: To be defined Hours: Full Time Placed On: 21/05/2025 Closes
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development. This unique nascent university, with its state-of-the-art campus and infrastructure, has woven a sound academic and research network, and its recruitment process is seeking high-quality academics
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development. With its state-of-the-art campus and infrastructure, this unique nascent university has woven a sound academic and research network, and its recruitment process is seeking high-quality academics
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infrastructures to enhance energy management, transportation networks, and urban sustainability. Key Responsibilities Design and implement digital twins to monitor and optimize urban systems, including
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candidate will be employed by Mohammed VI Polytechnic University (UM6P) based at Benguerir (50 km north of Marrakech), Morocco. The net salary per month is 2000 USD. The initial appointment as Postdoctoral
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innovation. This unique university, with state-of-the-art infrastructure, has woven an extensive academic and research network, and its recruitment process is seeking outstanding academics and professionals
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neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view learning, transfer learning, and data fusion techniques to integrate heterogeneous omics datasets