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Field
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Neuroscience (IoPPN). The centre aims to better understand the complex interrelationships between society and mental health, with a commitment to: Ensure that the impact of social context is central to how we
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processing, signal processing, and network resource management to enhance performance. To optimize and analyze complex 6G networks, we use AI/ML, graph theory, and optimization techniques Furthermore, our
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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of the Microverse” (www.microverse-cluster.de ), the CRC/Transregio 124 “Pathogenic Fungi and Their Human Host: Networks of Interaction” (www.funginet.de ) funded by the Deutsche Forschungsgemeinschaft and the
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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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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start her/his activities in ACER’s facilities at the UM6P campus in Benguerir and will then move permanently to the IART new R&D center at UM6P in the OCP chemical complex in Jorf Lasfar after
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healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics
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research projects aimed at (1) understanding the molecular mechanisms by which trabecular meshwork protein modifications induce fibrosis by transforming epithelial cells to myofibroblast-like cells (2
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EURL activities - Assist in method development and validation - Contribute to technical reports, research projects, and scientific publications - Liaise with network partners across Europe as part of