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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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repairing damaged extracellular matrix and initiating cartilage healing. We combine our expertise in light-driven chemistry, protein chemistry, tissue engineering, and process engineering to develop a
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phenotyping, including image analysis evaluations, for trait quantification Handle NGS datasets for RNAseq or SNP detection and linkage analysis using R Your qualifications and skills: You have a PhD or
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vitro infections, new infection models and live imaging methods Teaching: Organise, lead and conduct exercises, seminars and practical courses in genetics in accordance with the examination and study
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talents and passion as we work together to drive forward scientific progress. The Institute of Machine Learning in Biomedical Imaging (IML) focuses on pioneering research to harness the power of machine
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, molecular biology and fluorescence imaging will be preferred. We offer an interdisciplinary research environment that fosters innovation and collaboration and are committed to training and career development
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Max Planck Institute of Biophysics, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 2 months ago
analysis of SMC motor proteins (the candidate with prior experience in quantitative (imaging) data analysis is preferred. Prior experience in microscopy is desired but not required.) Development of 3D
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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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systems, organoid culture, orthotopic transplantations of cells/organoids, CRISPR/Cas9, molecular in vivo imaging, quantitative proteomics/phosphoproteomics, multiple transcriptomics and genomics approaches
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medical image data. Vivid Interest in interdisciplinary research, closely working together with pathologists, medical experts, computer scientists and other researchers. Independent and pro-active work