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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models
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methods (e.g. machine learning methods and many other methods) to harmonize historical and current pathogen nomenclature, standardize laboratory test methods and result vocabularies, and translate clinical
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The Department of Cell and Molecular Biology (ICM) (https://icm.uu.se) is organized into seven research programs, each focusing on distinct areas within cell and molecular biology i.e. computational
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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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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a
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at Sahlgrenska Academy of relevance include genomics, metagenomics, culturomics, proteomics, transcriptomics, software development, machine learning, and other statistical analyses of large-scale health data