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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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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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National Program for Data-Driven Life Science (DDLS) is a 12-year initiative that focuses on data-driven research, to train and recruit the next generation of life scientists and create strong and globally
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project in collaboration with AstraZeneca Chalmers University of Technology, funded through the Wallenberg National Program for Data-Driven Life Science (DDLS). Chalmers University of Technology conducts
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processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data Driven Life Science (DDLS) aims to recruit and train the next generation of data driven life scientists
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areas, such as scientific and educational development, leadership development as well as patent and innovation support. The position is part of the SciLifeLab Fellows program and will be placed within
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background in biology, programming or mathematics is meritorious. Knowledge in medical image processing, image registration, and large-scale analyses of genetic (including Mendelian randomization), protein, or
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efficiently interact in the interdisciplinary project. We seek candidates with a strong computer science, mathematics, statistics, or bioinformatics background and strong programming skills. Some previous
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Umeå University, Faculty Office of Medicine Together with The Laboratory for Molecular Infection Medicine Sweden (MIMS) and the SciLifeLab & Wallenberg National Program for Data-Driven Life Science
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stakeholders at all SciLifeLab sites in Sweden, e.g. representing the technology platforms, the national data centre, the operations office, the training hub, the data-driven life science (DDLS) research program