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research and methodological development to design and implement novel computational models and solutions. A solid theoretical background and hands-on experience in digital image processing and deep learning
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of image analysis and machine learning with a minimum of 90 higher education credits. Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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background in biology, programming or mathematics is meritorious. Knowledge in medical image processing, image registration, and large-scale analyses of genetic (including Mendelian randomization), protein, or
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), Opn4 and Opn5, as photoreceptors not directly involved in image-forming vision has opened up for non-visual opsin studies. Our recent publication, using GFP reporter mice, provides evidence of early
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data and clinical information. Applicants must hold (or be close to completing) a PhD in a relevant field and have expertise in modern computer vision and AI research. Experience with biomedical data
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/spheroid preparation, confocal microscopy, live-cell imaging, and super-resolution microscopy. The postdoc will also be responsible for image processing using custom-developed code and software, as
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flow cytometry, confocal imaging, and single-cell RNA-sequencing and functional ex vivo assays. As a PhD student, you devote most of your time to doctoral studies and the research projects of which you
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of existing structures. However, despite major research efforts, the effect of cracks on durability is still debated. Ongoing long-term tests will be combined with accelerated testing methods. X-ray imaging is
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: Molecular cloning RNA sequencing and data analysis Immunofluorescence imaging and confocal microscopy Live-imaging Image analysis Cell culture The following education and skills are required: PhD in biology