10 phd-in-mathematics Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY in Morocco
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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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, 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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functional digital twin environment. Contribute to industrial validations, results presentations, and scientific publications. Candidate Profile PhD in Mining Engineering, Industrial Engineering, Applied
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will focus on: Bibliographic review, Report and scientific publications. organizing workshop courses Skills required for the position: The candidate must have: PHD with skills in one of the following
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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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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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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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experimental results. Ability to work in interdisciplinary teams that involve experimentalists and modelers. Criteria of candidates: PhD in Chemical/Mechanical Engineering, Energy, Applied Chemistry, Applied
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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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. Contribute to the supervision of master and PhD students. Qualifications: Ph.D. in Earth Sciences, Remote Sensing, Physics, Applied mathematics, or related field. Strong background in land surface modeling