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analytical sciences. We are looking for talented people to join us. Your responsibilities include: Interdisciplinary research within the project "Complex and Competing Phenomena in Recycled Flame-retardant
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data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San
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, Heidelberg and Mannheim, our scientists collaborate across disciplines to unravel the complexities of disease at the systems level – from molecules and cells to organs and entire organisms. Through strong
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Their Human Host: Networks of Interaction” (www.funginet.de ) funded by the Deutsche Forschungsgemeinschaft and the consortium SynThera funded by the Carl Zeiss Foundation (www.synthera.eu/ ). We
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limited understanding of how tumors systemically impair immune responses. Meanwhile, traditional animal models often fail to capture the complexity of human immune-cancer interactions. This position
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of the Microverse” (www.microverse-cluster.de ), the CRC/Transregio 124 “Pathogenic Fungi and Their Human Host: Networks of Interaction” (www.funginet.de ) funded by the Deutsche Forschungsgemeinschaft and the
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government, administration and business in their efforts to adapt to climate change. It builds up a national and international network structure in order to integrate existing competences and knowledge, and to
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Python, for processing and interpreting complex proteomics data Familiarity with proteomics software for data analysis, visualization, and management Experience with biological samples (e.g., FFPE, plasma