100 phd-mathematical-modelling-population-modelling Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY
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Artificial Intelligence (AI), particularly in the development and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have
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using advanced geological modeling tools such as Datamine software, Leapfrog Geo and Surfer. Supervise MSc/PhD students working on related tasks. Publish high-impact papers and contribute to funding
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system for bacterial genomes using cutting-edge genomic language models. This project aims to adapt and extend transformer-based architectures to create a powerful tool for understanding and predicting
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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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techniques may be employed to support the modeling of uncertainty, along with the formulation and resolution of planning problems using stochastic optimization methods. Key Responsibilities The selected
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Expected Start Date: October 2025 Job Description We are seeking a highly motivated postdoctoral researcher with expertise in vanadium and rare-earth element (REE) recovery, thermodynamic modeling
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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
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interdisciplinary teams that involve experimentalists and modelers Criteria of the candidates: PhD in Chemical/Mechanical Engineering, Applied Chemistry, Applied Mathematics, Physics, or related disciplines, with
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, tensor analysis, and network science to foster the professional development of team members. Qualifications and experience essential PhD in Applied Mathematics in the fields of Numerical Linear Algebra
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embedded systems and hardware engineering teams to integrate AI models into the BMS. Optimize AI/ML pipelines for resource-constrained environments, including edge AI applications. Guide PhD students and