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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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developed the SPARCED pipeline to convert structured lists of species, parameters, and reaction types into an SBML (Systems Biology Markup Language) model file, and we created a model based on one
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in life science. The creative and research-intense environment contributes to a broad knowledge-base as well as cutting-edge expertise. In addition, Uppsala University has a highly developed innovation
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, providing a platform to identify and optimize therapeutic candidates. Our group specializes in developing technologies to assess the multicellular environment within three-dimensional microtumor models
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Taheri Lab and the Lundberg Lab, funded by the Digital Futures (DF). The position is based at KTH Royal Institute of Technology and SciLifeLab (Science for Life Laboratory). KTH is Sweden’s largest
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contribute new and better ways to analyse and interpret large-scale data. In your position, you will develop computational methods for cryo-EM reconstruction, heterogeneity analysis, and modeling of structural
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, and develops various tools for bioimage analysis, mostly using machine learning and AI-based models. As a postdoc you will conduct research using various methods in cell-and molecular biology, but
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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be
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, and ERC Consolidator grant (DETOXPEST) and aims to establish a public, cross-species “pan-terminome” knowledge base of plant proteoforms and to uncover how conserved proteolytic processing
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Lund University Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 47 000 students and more than 8 800 staff based in Lund