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. Investigate the interactions between soil microbes and their environment using field and laboratory experiments. Analyze data on soil microbiomes, nutrient cycling, and soil biological processes. Develop models
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of process modeling software (e.g., Aspen Plus, COMSOL, or equivalent) is a plus. Excellent written and oral communication skills in English. Ability to work independently and as part of a multidisciplinary
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; Assess the effects of organo-mineral management on soil biological parameters, including soil fauna; Predict the dynamic of OM in the future global climate change by using Soil Organic Models. Mentor
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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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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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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