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research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves
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, (bio)informatics, and multimodal data analysis. The research group focusses on the mechanisms of Hypothalamic-Pituitary-Gonadal (HGP) axis regulation that governs human reproduction. The group
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-based workflow including Spatial GSA and statistical methodsEnhance monitoring accuracy and validate numerical models using field data The Doctoral researcher will be supervised by Prof. Lavasan, and will
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within the project AI4TECSWriting a doctoral dissertation in computer sciencePublishing research findings in leading international conferences and high‑impact journals in AI, machine learning, and
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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, (bio)informatics, and multimodal data analysis. The research group led by Dr. Johanna Raidt focuses on the identification of known and novel MMAF- and PCD gene variants using large patient cohorts
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in vitro work, including work with primary cells isolated from human bone and bone marrow, and characterize these primary cells using various cell biology and molecular biology methods Establish data
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Differentiate iPSCs into midbrain dopaminergic neurons and organoids for phenotyping and compound testing High content imaging and automated image-analysis Analyze omics data Collaborate closely with
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combine interdisciplinary research in molecular, structural, and cell biology as well as in physiology, biophysics, epi /genetics, (bio)informatics, and multimodal data analysis. The Eble group investigates
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state-of-the-art approaches, including next-generation sequencing, functional genetic screens, and transgenic model systems. Further information is available on our homepage and via our publications in