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valorization is essential. Required Knowledge: Solid knowledge of acid-base equilibria, and carbonate system modeling. Good understanding of calcium carbonate behavior and dissolution kinetics. Hands
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, comminution modeling, and ore characterization, and will contribute to developing an integrated beneficiation strategy that reduces operational costs, and energy consumption. This research aligns with broader
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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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selected researchers will contribute to both experimental and modeling activities involving sorption and condensation technologies, solar thermal integration, and system optimization. Responsibilities will
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for conducting research on climate variability assessment and hydrological modeling at the catchment scale. The selected candidate will engage in cutting-edge research that bridges the disciplines of climate
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digital twins to develop innovative solutions for monitoring, analyzing, and optimizing urban systems in real time. The candidate will contribute to modeling interactions between physical and digital
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
disorders, and microbiome-related health issues by applying advanced AI/ML techniques for biomarker discovery and metabolic network modeling. Scientific Challenges Addressed in the Position: High
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efficiency, ion separation rates, energy consumption, etc. Model ion transport and system behavior under different operational conditions. Collaborate with researchers in diverse projects and contribute
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develop innovative solutions based on the analysis of urban data (big data, IoT, GIS) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing
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for comprehensive systems biology modeling. Identification of causal relationships and biomarker discovery through integrative approaches. Time-series and longitudinal multi-omics data analysis for disease