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they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale
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, fundamental and strategic plant biology research is conducted on wild species, agricultural crops, forest trees, bioenergy crops, and model organisms. Our main research areas include genome analysis
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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life science technologies with data and AI expertise. Computational methods and artificial intelligence applied to large-scale molecular data are transforming the study of biological systems at all
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The Department of Medical Biosciences is offering a postdoctoral scholarship within the project “Developing computational tools for large-scale human intracellular signaling models”. The scholarship
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accessibility data will also be developed. The framework will be addapted and applied to spatial data to connect the GRN models to specific tissue phenotypes and to gain a better understanding of e.g. cancer
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includes designing fusion proteins with various tags, producing viruses, transfecting human cells, and studying how these cell models are affected by small molecules and intracellularly produced peptides
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contribute new and better ways to analyse and interpret large-scale data. In your position, you will develop computational methods for cryo-EM reconstruction, heterogeneity analysis, and modeling of structural
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, volumetric analysis, and modeling of structural heterogeneity in biological macromolecules. Rather than only applying established workflows, you will explore new computational formulations and alternative ways
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internationally outstanding research in the life sciences. Project description We seek two highly motivated postdoctoral researchers to develop new mathematical and computational methods for modeling developmental