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cancer Establish single-cell perturbation screening approaches to investigate cell fate decisions and disease mechanisms Integrate high-content imaging, single-cell transcriptomics, and functional assays
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culturing, integrating multiple automated subsystems with image-based machine learning models. Our objective is to enable robotic decision-making through machine learning, paving the way for a standardized
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parameters as well as novel AI-supported parameters) for multimodal, image-supported control of diagnostic-therapeutic processes, taking into account the latest imaging methods in close interdisciplinary and
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/continued employment is being sought) Contract:TV-L Your tasks As a key member of our interdisciplinary team, you will: Harness a comprehensive dataset spanning digital pathology images, methylation profiles
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process A wide range of opportunities for further training and career development Remuneration for the position is based on pay group 13 TV-L. The contract is limited to 24 months. For further questions
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bioinformatics workflows to integrate spatial proteomics, spatial transcriptomics, and digital pathology images, enabling the assessment of cellular heterogeneity and tissue architecture in brain cancer. Combine
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“ an Prof. Dr. Alexis Maizel per E-Mail als PDF-Dokument an bewerbungen@cos.uni-heidelberg.de senden. Die Die Universität Heidelberg steht für Chancengleichheit und Diversität. Wir bitten qualifizierte
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Med 2025). We are particularly committed to advancing precision medicine through cutting-edge molecular diagnostics. Our interdisciplinary team of physician scientists, molecular biologists, data
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research and teaching in an international environment. Our work is supported by the CellNetworks Core Technology Platform (Deep Sequencing, Nikon Imaging Center, Electron Microscopy and Metabolomics). A
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research and teaching in an international environment. Our work is supported by the CellNetworks Core Technology Platform (Deep Sequencing, Nikon Imaging Center, Electron Microscopy and Metabolomics). A