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candidates will be based on their capacity to successfully complete the program. Important criteria when assessing this capacity are; documented knowledge and skill in the field of the thesis project, written
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition. Lund University welcomes applicants with diverse backgrounds
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to the project. The ranking of applicants will be based on undergraduate grades, on the undergraduate education profile and on any additional experience of research in areas of relevance for the research project
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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information. The techniques include image registration, segmentation, and regression/classification, often include deep learning-base implementations. Together with experts in epidemiology, genetic, and multi
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position is available for a motivated student with experience in biostatistics, molecular epidemiology, biomedicine and large-scale computational analysis. The position is based in the research group led by
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an individual study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required. The research group The position is based in Joakim Dahlin’s team at Karolinska Institutet
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collaborations. The research group The position is in Ben Murrell’s group in MTC, based in the Biomedicum, in Karolinska’s Solna campus. The lab has worked across the experimental/computational interdisciplinary