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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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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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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
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on Earth is a laboratory that has operated for billions of years, producing remarkably diverse, complex, and robust biological systems; however, significant challenges persist in understanding