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HBIGS Heidelberg Biosciences International Graduate School | Heidelberg, Baden W rttemberg | Germany | 8 days 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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, longitudinal patient and population registries and biobanks. Project description The development of artificial intelligence (AI) and computerised image processing in combination with advanced digital microscopy
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Delft. In this team, consisting of several PhD students, postdocs and undergraduates, we focus on developing new concepts for 3D imaging of nanostructures, using light. Job requirements A masters degree
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to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
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to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
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School Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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public, and to critically engage with the scientific community. The applicant will work in close collaboration with the other PhD students, postdocs, and researchers in the Engblom and Lundeberg labs
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Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM components are in use
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medical imaging, where location can both reveal crucial patterns and pose privacy risks. You will develop and study privacy-preserving methods (e.g., differential privacy and synthetic data) that allow