21 postdoctoral-machine-learning "Mohammed VI Polytechnic University" Postdoctoral positions in Morocco
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. The primary objective is to design robust and efficient planning solutions—integrated within a digital twin—that account for the uncertainties and variability inherent in industrial processes. Machine learning
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About UM6P: Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields
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in Operations Research. Strong skills in Machine Learning. Practical experience in mining or industrial environments (through projects, thesis, or postdoctoral work). Ability to work effectively in a
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. The successful candidate will develop advanced machine learning (ML) models to automate and optimize retrosynthetic analysis, facilitating the discovery of efficient and sustainable synthetic routes for complex
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Mohammed VI Polytechnic University - Benguerir - Morocco Geology & Sustainable Mining Institute GSMI About the employer Mohammed VI Polytechnic University is an institution dedicated to research and
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Institution Overview: Mohammed VI Polytechnic University is dedicated to research and innovation in Africa and aims to be recognized among the world's leading universities in its fields
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Institution Overview Mohammed VI Polytechnic University is a leading research and innovation institution in Africa, committed to economic and human development. The university places research and
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(especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning, particularly for multi-variable simulations. Knowledge of complex systems
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, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
, and Precision Health. The project aims to leverage AI and machine learning (ML) to analyze complex metabolomics datasets and address key health challenges, including biomarker discovery, disease