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learning paradigms as well as interactive data- and model exploration with domain knowledge towards optimal performance in real-world generalization scenarios. AqQua is a large-scale collaborative research
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training students Maintain analytical equipment Cooperate with other large collaborative projects of the research group Qualification: Required: A diploma and a PhD in microbial natural product chemistry
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of the extracts; LC-MS and bioactivity-guided isolation and structure elucidation of the purified metabolites Supervising and training students Maintain analytical equipment Cooperate with other large collaborative
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ICR groups. There will be a possibility to collaborate with local spin-offs. For further information, you can contact Dr. Réka Markovich () and Prof. Leon van der Torre (). Your profile A PhD in
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. A major focus will be on the identification of small molecules from mass spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available
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within our portfolio of hypothesis-generating screening studies, a methodological portfolio where we identify signals of interest from real-world register data to guide the conduct of tailored studies. We
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
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immunological assays are developed and conducted, and The Biomedical Laboratory at SDU, which houses state-of-the-art small- and large animal facilities. The postdoc will join the group of Professor T. E
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the development of computational methods for genetics, high-throughput omics data and causal discovery. Our interdisciplinary and international team is jointly located at DKFZ and EMBL Heidelberg, and
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Postdoc in Psychiatric Epidemiology: Linking Register and Trial Data to Study Postpartum Depressi...
digital treatment of maternal postpartum depression also benefits child outcomes. Initially, the postdoc will focus on conducting register-based studies using national health and administrative data. As the