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Field
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approaches to large-scale biomedical data. Research topics may include foundation models for longitudinal electronic health records and genomics, multimodal learning integrating health records with molecular
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candidate is expected to develop an independent research programme within this broad scope, focusing on methodological innovation and the application of modern AI approaches to large-scale biomedical data
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chickens’ Campylobacter susceptibility. The postdoc will have a leading role in the large-scale multi-omics (“hologenomic”) data analysis to integrate/synthesize the genomic, transcriptomic, metagenomic, and
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resistance mechanisms, and identify actionable vulnerabilities. We integrate longitudinal patient cohorts with single-cell and bulk multi-omics, liquid biopsy, and patient-derived models, partnering closely
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problems, scale solutions, and drive impact. Real Learning for Real Impact. To reinforce our team, we are looking for a Research Fellow: Natural scientist or engineer wanting to make a difference in
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, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas from lab to society
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cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical data across multi-institutional research networks, with a focus on the analytical and
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biology, or other AI-related disciplines. The successful candidate will join a dynamic, interdisciplinary team focusedon developing and applying novel AI and statistical methods for multi-omics data
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the broader areas of multi-modal learning analytics, AI in education, and (computer-supported) collaborative learning. The successful candidate will join the interdisciplinary DFG-funded project AEyeCoL
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: The Centre for Research in Child Development (CRCD) is a leading research centre dedicated to advancing understanding of child development and early education. CRCD conducts multi-project research to generate