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systems for diagnostics and treatment. Core activities include signal processing, antenna design, and measurement hardware development. Building complete prototype systems for clinical testing is a central
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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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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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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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combining imaging techniques and data analysis 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
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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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relevant. Our group approaches this question from a novel perspective, by studying the role of transposable elements (TEs) in this process. TEs occupy 50% of the human genome and are known to be very strong
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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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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