144 machine-learning-modeling-"Linnaeus-University" Postdoctoral positions in Morocco
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) combined with machine learning and chemometrics. Key Responsibilities: The Postdoctoral Researcher is primarily intended to support leaf spectroscopy research but will also be involved in other research
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skills/programming/modeling would be a plus. Candidate Criteria Ph.D. in Chemical engineering or a related field. Extensive experience in unit operations and chemical processes. Ability to design and
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terms of research and education, covering all aspects of computer science, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs
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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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. 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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diagnosis. These tools will leverage various spectroscopic techniques (VNIR, SWIR, and XRF) combined with machine learning and chemometrics. Key Responsibilities: The Postdoctoral Researcher is primarily
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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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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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, 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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(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