19 machine-learning-modeling Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY 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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. 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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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation
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, emissions, and productivity. Decision-Support & MCDA Implement a machine-learning-driven multi-criteria decision analysis to rank and select optimal decarbonization pathways. Collaborate with industry and
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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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, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs Summary: UM6P invites applications for post-doc, in all areas of Computer Systems. A
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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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, Agronomy, modeling, biostatistics, or related field The applicant should have documented knowledges in Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming
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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