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science, automation science, or a related field, and convincing expertise in robotic hardware. Experience with machine learning and large language models is highly desirable. Prior experience in a biological setting
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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key
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. Central to its objectives is the development of methods for culturing tailor-made organoids, assembloids and co-organoids for inter-organ communication towards AI-supported large-scale / high-throughput
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. Central to its objectives is the development of methods for culturing tailor-made organoids, assembloids and co-organoids for inter-organ communication towards AI-supported large-scale / high-throughput
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the world. We are seeking a highly motivated Postdoctoral Researcher with expertise in large-scale omics data analysis to establish an innovative multi-omics data integration workflow. This unique position
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Heidelberg University and Stanford University, including population health researchers, clinicians, and methodologists. The researcher will lead analyses in large-scale electronic health record data
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expertise and achieve optimal results. Your Profile A PhD in Bioinformatics, Computational Biology, or a related field. Proven experience in large-scale omics data analysis, preferably MS-based proteomics
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Fiedler. Your tasks: You will be responsible for performing and analyzing experiments with ICON, Germany’s next CMIP model, and the scientific analysis of big data sets from model experiments and