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. Merits for this position: PhD acquired within three years of last application date. Documented pedagogical experience. Experience in image analysis and/or computer vision, especially in the context
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and molecular genetics as well as hands-on experience with cloning, live-cell fluorescence microscopy, image analysis, and sample preparation for sequencing and multi-omics analyses. The main model
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and project developers in reusing them in new projects. Taking the Chalmers campus as a starting point, we are developing scalable, AI-powered methods, such as computer vision for street-view imagery
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transferable and interpretable models for tabular data, efficient learning paradigms for medical imaging, and causally grounded and identifiable representation learning. You will have great freedom to influence
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new ways of processing information - far beyond the limits of classical systems. Our research spans quantum computing, sensing, transduction, thermodynamics, and foundations, all aimed at harnessing
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to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical, biological, and methodological
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documented experience in computer vision, where the PhD project was fully or substantially method-focused on computer vision and/or AI-based image or video analysis have very strong knowledge of machine
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other relevant qualifications A high level of computer proficiency, particularly in advanced imaging and image analysis, FACS, in vitro and/or in vivo assays Very high motivation, ambition and enthusiasm
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engineering processing, material recycling, nuclear chemistry, theory and modelling. About the research project The project focuses on the development and synthesis of new π-conjugated organic semiconductors
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the underlying principles. For us, it is equally important to study the impact of materials on biological processes as well as the impact of biological processes on materials. Our ambition is to foster a dynamic