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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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perform one or both de- and re-conjugation, what determines a cell’s choice between de- versus re-conjugation, and under which specific conditions bacteria preferentially perform one versus the other
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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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multiple disciplines. The international and collaborative atmosphere at the Max Planck Institute of Biochemistry, together with our group’s close connections to leading university hospitals in Munich
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and able to work collaboratively and across different disciplines. Any questions concerning the role and/or queries regarding the relevant terms and conditions should be addressed to recruitment
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skills; Enthusiastic team player and able to work collaboratively and across different disciplines. Any questions concerning the role and/or queries regarding the relevant terms and conditions should be