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fellow in data-driven cell and molecular biology. For more information about us, please visit: DBB and MBW Data-driven life science (DDLS) uses data, computational methods and artificial intelligence
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research school for 260 PhDs, including industry PhDs and postdocs. Fellows are recruited to the 11 participating host universities/organizations, but brought together under the DDLS program, which has four
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. NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by
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Do you want to contribute to improving human health? Computational methods and artificial intelligence on large-scale molecular data are transforming the study of biological systems at all levels
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Do you want to contribute to top quality medical research? Computational methods and AI applied to large-scale molecular data are transforming biology – from molecular structures and cellular
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General description of the DDLS Fellows programme Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels
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to user needs and scientific questions. Qualifications Qualification requirements: A university degree in computer science, physics, engineering, bioinformatics, or a related field (PhD degree is
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visualizations tailored to high-dimensional multi-modal spatial data. Qualification requirements Required Qualifications A PhD (or MSc with significant experience) in Bioinformatics, Computational Biology, Systems
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. You are structured, like to collaborate and communicate well with others in a responsive and flexible way. The following education, experience and expertise are required: PhD in a relevant subject e.g
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Experience A PhD in bioinformatics, computational biology, systems biology, or a related field, or equivalent scientific expertise Proficiency in Python and R, particularly for data analysis, visualization