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and computational modeling to understand complex biological processes. Experience in statistical modeling, machine learning, or analysis of spatial or high-dimensional biological data is considered
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advanced biostatistics/machine learning analyses, but also with other types of analysis. The work involves supporting Swedish researchers under a “user fee-based” support model. The projects will differ in
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Image Science and Visualization (CMIV), Linköping University Hospital. Your office will be at CMIV, which is instituted to serve as a melting pot and meeting place between academia, industry, and
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, including high-throughput screening, high-content imaging, omics technologies, and computational approaches, to elucidate mechanisms of toxicity. Ultimately, our work contributes to a deeper understanding of
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work will increasingly focus on wet lab experiments using cancer cell lines, organoids, and animal models, including imaging and molecular analysis. The project is well-suited for candidates with a
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Spatial metaTranscriptomics methods and thus also handling of image data. The PhD student will interact with other team members to a large extent. For this purpose, we are looking for a PhD student with
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will use machine learning methods to develop affinity ligands. These methods have been transformative for protein design, allowing generation of novel proteins which can suit a precise need. In this 4
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administrative support systems Solid computer skills and proficiency in Microsoft Office (including Excel), and the ability to adopt new digital tools is required. Fluency to express yourself in speech and writing
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artificial intelligence (AI)/Machine Learning (ML) with a focus on life science, or alternatively, life science with a focus on AI/ML (or equivalent). You will work closely with researchers, engineers, and
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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