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developing complete models. Example applications include microscopy image data, cryo-electron microscopy, structural prediction and dynamic simulation of biological macromolecules, genomics data, and
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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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or explainable AI or safety). Experience in machine learning, causal inference, image processing, human-robot interaction, or large language models. Experience in analyzing multimodal data (e.g., text, sensor
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at the same time so special. The originality of the experiments is in the combination of X-ray based scattering and imaging methods to monitor the changes at the particle scale during testing. Research
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research on protein aggregation, and state-of-the-art imaging techniques. We anticipate this postdoctoral fellowship will contribute to impactful research in the field of neurodegeneration. The project
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of scientific data, e.g. from image acquisition modalities or scientific simulations. Efficient algorithms are at the core of most of these data analysis and visualization applications. The focus of this Ph.D
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School of Engineering Sciences at KTH Job description The research project concerns the development and use of MINFLUX single-molecule microscopy for cellular imaging and dynamic studies
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to improve our understanding of fundamental processes relevant to combustion engines, gas turbines, and fire safety. The successful candidate will join a dynamic and diverse research group with an extensive
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research is based on large and high-dimensional datasets across multiple modalities, including molecular, clinical and histopathology imaging data. Our computational pathology research is based
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, particularly in applying advanced screening tools, such as high-content imaging (Cell Painting) to uncover effects of exposure to (nano)particles and chemicals. The position is hosted by the School of Medical