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and Wallenberg National Program for Data-Driven Life Science (DDLS) (https://www.scilifelab.se/data-driven/ ) aims to recruit and train the next generation of data-driven life scientists and to create
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computational scientists – both nationally and internationally. In addition, the doctoral student will be part of the data-driven life science initiative. The data-driven life science initiative Data-driven life
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long-lasting adverse health effects in humans and wildlife is also performed. For more information see www.iob.uu.se Data-driven life science (DDLS) uses data, computational methods and artificial
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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 globally leading computational and data
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science, computer science, bioinformatics, or a related subject relevant to the position or documented experience that can be deemed equivalent. Experience of development in Linux-based environments
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an equivalent degree from another country. Assessment criteria Particular emphasis will be placed on scientific excellence. Experience and expertise in computational analysis, documented competence in
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fields and access to various scientific and technical expertise. All PhD students at the Faculty of Medicine attend the doctoral education program. More information about the program can be found
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at the Wallenberg Laboratory. The group is part of the national Data-Driven Life Science (DDLS) program, funded by the Knut and Alice Wallenberg Foundation. Their research focuses on developing computational methods
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at the Wallenberg Laboratory. The group is part of the national Data-Driven Life Science (DDLS) program, funded by the Knut and Alice Wallenberg Foundation. Their research focuses on developing computational methods
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. The research group is part of the National Program for Data-driven Life Science (DDLS), generously funded by the Knut and Alice Wallenberg Foundation: www.scilifelab.se/data-driven/ Our group focuses on studying