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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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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 and to create
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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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and expertise will strengthen an application: proven experience with Unix command-line interface (CLI) and Bash scripting proficiency in a higher-order programming language like Python or R experience
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intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for
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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
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) programme and research school Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures