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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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questions we aim to tackle as part of this project are: Why are only some bacteria capable of performing one or both processes? Under which environmental conditions do organisms that can execute both
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list of questions we aim to tackle are: Why are only some bacteria capable of performing one or both processes? Under which environmental conditions do organisms that can execute both modifications
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summaries (visualizations) using relevant computer software; Assisting with preparing grant applications to secure further funding for relevant projects; Helping establish new projects and research consortia
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(visualizations) using relevant computer software; Assisting with preparing grant applications to secure further funding for relevant projects; Helping establish new projects and research consortia relating