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Description Open one or two year Postdocs positions on Surrogate Models for Uncertainty Quantification (UQ), at the Centro de Investigación en Matemáticas (CIMAT-SECIHTI, México). We are a UQ research group
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Learning for Biomedical Data. The postholders will focus on developing and applying state-of-the-art generative models (such as VAEs, GANs, and transformer-based architectures) to large-scale biomedical
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modification. By marrying first-principles theory – trade-off analysis, game theory, reaction-diffusion, and consumer-resources models – with single-cell tracking and synthetic community experiments
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) analysis Mathematical modelling Microbiology Molecular biology We approach science with the view of physics, aiming to identify principles behind complex systems. We collaborate closely with engineers
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% women; three continents represented). The strengh relies in coupling: Single-cell microfluidics Quantitative (image) analysis Mathematical modelling Microbiology Molecular biology We approach science with