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under different climatic and social contexts to provide decision-making tools for sustainable urban planning. Main Tasks and Responsibilities: Develop a predictive model integrating the direct and
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sensor data, public databases, and GIS. Predictive Modeling:Design predictive models to evaluate the impact of urban and environmental policies on public health. Interdisciplinary Collaboration:Collaborate
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levers to reduce costs and lead times. Develop strategies and risk management models to enhance the system’s resilience against logistical disruptions. Implement energy management approaches and CO
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combined with modeling experiments or enhanced research in parameterization, AI is accelerating computational processes, improving prediction accuracy, and enabling the creation of extensive model ensembles
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system for bacterial genomes using cutting-edge genomic language models. This project aims to adapt and extend transformer-based architectures to create a powerful tool for understanding and predicting
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
analysis for monitoring disease progression and treatment outcomes. Key Responsibilities: Develop and implement AI/ML pipelines for feature selection, dimensionality reduction, and predictive modeling using
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interfaces, and condensation surfaces under varied operating scenarios. Develop and refine performance simulation models and predictive tools to support system optimization and deployment strategies. Prepare
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networks, metabolic networks) to identify key disease drivers and biomarkers. Build predictive models for disease classification, patient stratification, and treatment response prediction. Collaborate with
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way to represent a graph is to use the adjacency matrix associated with the graph. However, adjacency matrices only model networks with one kind of objects or relations between the objects. Many real
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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