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21 Aug 2025 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Computer science Mathematics Researcher Profile Recognised Researcher (R2) Established Researcher
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. Mathematically, a network is represented by a graph, which is a collection of nodes that are connected to each other by edges. The nodes represent the objects of the network and the edges represent relationships
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of the extraction and beneficiation system. This work will require an understanding of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict
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a member of a team in a collaborative environment. Strong mathematical and analytical skills. Strong technical background in optimization in wireless communications/networking. Experience with
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Mathematics, Data Science, or related fields. Strong background in Operations Research. Experience with industrial data processing, particularly in dynamic, real-time environments. Proficiency in machine
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Département / Department : Unité / Unit:Center for African Studies Université / University:Mohammed VI Polytechnic University Intitulé de l’offre Postdoc / Title of the Postdoc offer : L’Afrique dans l’œuvre de Mokhtar Soussi Summary of the subject: One of the missions of the Center for African...
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, transportation systems and biological interactions. These systems are represented as networks. A network is a set of objects that are connected to each other in some fashion. Mathematically, a network is
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: Mathematical Modeling: Develop mathematical models to simulate and optimize the entire waste management chain—from collection to treatment. Data Integration and Analysis: Integrate real-time and historical data
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part of the project team. Applicant requirements Ph.D. in bioinformatics, proteomics, drug design and development, genomics, mathematics, computer science, or related fields Complete CV Short research
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of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions. 2. Key Responsibilities