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scientific field (e.g. computer science, data science, mathematics, statistics, engineering, physics, or related). Provable deep learning track record and practical expertise (e.g. with VAEs, GANs, diffusion
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at the intersection of machine learning, CRISPR screening data analysis, and multi-omics to uncover genetic interactions and synthetic lethalities in cancer. Develop and apply scalable, reproducible computational
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interdisciplinary research projects in collaboration with experimental labs. Being closely involved in the experimental design, data generation process, and analysis. Writing efficient, reusable, and elegant code
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mathematics, physics, geophysics, optical engineering, electronic science and technology, chemistry, materials science, biology, bioengineering, pharmacy, basic medicine, environmental science and engineering
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at the intersection of machine learning, CRISPR screening data analysis, and multi-omics to uncover genetic interactions and synthetic lethalities in cancer. Develop and apply scalable, reproducible computational
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data analysis in line with the research group’s objectives. Grow your skills Postdoctoral researchers engage in cutting-edge research in the life sciences, collaborating with interdisciplinary teams and
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with RNA-seq procedures and analysis (short- and/or long-read preferred) Familiarity with splicing regulation, RBPs, or 3′UTR biology is a plus Comfort working with mouse models and brain tissue (e.g
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appropriate analysis strategies for genetic and ‘omic data integrated into epidemiological investigations; Collaborating with external (including many international) researchers to lead or contribute to large
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and the upgrading of traditional vaccines, breakthrough the key technical bottlenecks in basic research, process development and production of vaccines, continuously optimize the industrial structure