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Area of research: Scientific / postdoctoral posts Job description: Postdoc for "Large-Eddy Simulations of Arctic air-mass transformations" (m/f/d) Background The Arctic climate is shaped by
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sequence data for fungal plant pathogens within the Dothideomycete family. The lab has an existing fungal collection of over 40 strains collected from wheat, wild-grasses and barley. Ideal candidates will be
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microscopy data analysis, chemometrics, and machine learning. This position is ideal for a researcher who enjoys working at the interface of imaging, data science, and environmental monitoring. The project
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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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. 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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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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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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or related with strong bioinformatics background) (m/f/d) with focus on the analysis of cutting-edge liquid biopsy proteomics, transcriptomics and other omics data sets related to blinding diseases, such as
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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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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