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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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spectrometry imaging (MSI) of brain tissue. The missingness can happen along two dimensions: spatial (super resolution) and feature (data imputation). Enhancing the quality of MSI advances our understanding
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KTH Royal Institute of Technology, Scool of Electrical Engineering and Computer Science Job description Cellular morphology reflects fundamental biological processes such as division
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super‑resolution microscopy and quantitative live-cell imaging using diverse fluorescent reporters in cultured cells and early embryos. These experimental approaches are integrated with advanced image
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++ or similar) and an interest in quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not
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fluorescence microscopes and the Xenium in situ platform. Office work involves image data processing and analysis, as well as preparing project reports. For more details about the facility, visit
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-driven life science framework. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for
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complex biological processes. This project combines timely analytical challenges with deep rooted applications in life science. We are looking for a candidate with a PhD in either engineering/computer
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artificial intelligence applied to large-scale molecular data are transforming the study of biological systems at all levels, from molecular structures and cellular processes to human health and global