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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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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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/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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of methodologies, from in-depth behavioral assessments to computer vision, machine learning and neuroimaging techniques, we aim to uncover the complexites of neurodevelopmental disorders. Our
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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