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discovery by integrating artificial intelligence with synthetic biology to target “undruggable” proteins. The project is a collaboration between the national SciLifeLab Drug Discovery & Development platform
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studies. About the DDLS program Data-driven life science (DDLS) combines data, computational methods, and artificial intelligence to study biological systems from molecular structures to human health and
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artificial 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
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Alice Wallenberg Foundation, with the objective of building globally competitive research environments at the interface of life science, data science, and artificial intelligence. The postdoctoral program
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-driven life science framework. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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together with their supervisors, as well as with other doctoral students and postdocs in the supervisors’ groups. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence
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to receiving your application! 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
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-supervisors, as well as with other doctoral students and postdocs in the supervisors’ lab. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological
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Infrastructure (SBDI) and maintains the Swedish Species Observation System. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes
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ambitious research initiatives, focusing on using data, computational methods, and artificial intelligence to study biological systems, offering ample opportunity for networking and collaboration. Access