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transcription machineries, auxiliary transcription factors, chromatin remodellers, SMC complexes and transposable elements affect genome structure. We are seeking an ambitious, highly motivated Postdoc with a
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human health. Within this mission, the Funke group is developing machine learning methods for automatic and semi-interactive analysis of biomedical image datasets, concretely: (1) semantic and instance
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to accelerate biomedical discovery. Our mission is to transform bold scientific ideas into advances that improve human health. In this context, the Funke lab develops machine learning methods to accelerate
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human health. Within this mission, the Jug Group develops advanced computational methods and open scientific software to extract knowledge from complex biological imaging data. We work at the intersection
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mapping, scalable manipulation of individual regulatory elements, and single-cell, isoform-sensitive measurements of translation in vivo. We are recruiting highly motivated and talented scientists who will
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software engineers, as well as collaborating closely with research groups in the institute that work to develop new image analysis methods. Contributing to the development of open-source tools in
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analysis methods into user-friendly software and service packages. Collaborating with team members and the community to maintain essential open-source software for bioimage analysis. Human Technopole
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& Utilization of Resources; (2) Cycling and Extraction of Key Metal Elements; (3) Recycling of Wind, Battery, and Photovoltaic Equipment; (4) Energy Conversion and Storage; (5) Energy-saving Materials and
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methods for integrative analysis of large-scale perturbation and omics datasets, translating results into experimental strategies in close collaboration with wet-lab teams. Drive scientific output and
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, molecular epidemiology, statistical genetics, biostatistics, health data science, etc) or to be obtained within the next 6 months; A sound understanding of applying relevant statistical methods to highly