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Overview An opportunity has arisen for an experienced image analysis and computing scientist with experience in both classical image processing and artificial intelligence to work as part of
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HBIGS Heidelberg Biosciences International Graduate School | Heidelberg, Baden W rttemberg | Germany | 1 day ago
criteria Significant experience with confocal microscopy, and (plant) molecular biology. Selection process Please check out all the cool research projects in high resolution plant imaging of the nucleus and
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-Talisman Lab, please click here . As a successful candidate, you will: Purify EVs from cultured cells and plasma using different analytical platforms. Perform imaging experiments using super-resolution
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slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and demonstrated experience in computer vision or analysis of pathology images
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processing and image representation Demonstratable experience in python for data handling and algorithm development Desirable : Knowledge and experience with imaging systems (X-ray CT, MRI or similar
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-trained tool on other image sensors and at different mountain sites presents difficulties. Specifically, generalizing a model trained on a specific site to other sites with different environmental
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-guided Linac and PET-guided linac, Varian Ethos with adaptive radiotherapy capabilities. Different imaging simulators are also available within the department including CT, PET/CT and MRI. Research is
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analysis Experience working with R and Python for data analysis and image processing Familiarity with image analysis tools (e.g., ImageJ/Fiji, CellProfiler, or similar platforms) is desirable Education and
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researchers claim the total electron dose required to reconstruct an image could thus be reduced by factors of 2, 10 or even 100. Modern digital scan units can implement different scan procedures without
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models of image processing; (iii) demonstrate experience in academy-industry projects; (iv) interest in publishing high-quality journal papers in the field; (v) demonstrated leadership in research projects