186 phd-in-architecture-landscape-built-environment Postdoctoral positions in Morocco
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African continent. With a strong focus on research and innovation to support education and sustainable development, UM6P boasts a state-of-the-art campus and infrastructure. It has built a robust academic
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: Design and implement AI/ML pipelines for multi-omics data integration, including supervised and unsupervised learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph
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platform for experimentation and a pool of opportunities, for students, professors, and staff. It offers a high-quality living and study environment thanks to its state-of-the-art infrastructure. About
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at the intersection of numerical linear algebra and advanced HPC. The candidate will join an international environment, with opportunities to collaborate with experts from the USA, and KAUST and publish in top-tier
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platform for experimentation and a pool of opportunities, for students, professors and staff. It offers a high-quality living and study environment thanks to its state-of-the-art infrastructure. With
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platform for experimentation and a pool of opportunities, for students, professors, and staff. It offers a high-quality living and study environment thanks to its state-of-the-art infrastructure. About
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70 km away from Marrakech. Thanks to its prestigious architectural landscape and modern equipment, the UM6P offers premium conditions for a desirable lifestyle. DESCRIPTION OF GSMI: GSMI (Geology
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-oriented research environment in the metropolitan area of Marrakech. Job description: The Agricultural Innovation and Technology Transfer Center (AITTC), part of the College of Agricultural and Environmental
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nutritional security. About the PHENO-MA Platform: The PHENO-MA is an innovative research platform for high-throughput plant phenotyping built and established at the University Mohammed VI Polytechnic (UM6P) in
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for parallelism in the tensor completion process to enhance computational efficiency. Investigate parallel algorithms and architectures that can exploit the inherent parallelism in tensor operations. Collaboration