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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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, 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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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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++ 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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-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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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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research. The university is fully committed to and make use of national molecular bioscience infrastructures, including SciLifeLab platforms for genomics, proteomics, imaging, bioinformatics, and high
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molecules, genes, individuals, species and their life conditions, evolution and interactions in the environment. The focus should be on patterns and processes that previously have been difficult to study, but
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upon Join us! The Department of Materials Science and Engineering aims to be an environment for successful and valuable research and education with a focus on materials science solutions for important