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cellular 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
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-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 processes to human
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Referensnummer IFM-2026-00053 Work assignments This PhD position focuses on methodological and computational development in cryo-electron microscopy (cryo-EM), with emphasis on image reconstruction
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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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, from molecular structures and cellular 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
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structures and cellular 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
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to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for DataDriven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to
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an international, stimulating, and collaborative research environment where your scientific career development is promoted. The project aims to track strain wide differences within human gut bacteria species in
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Learning) and Associate Professor Sofia Mikko (SLU). The supervisory team brings expertise in computer vision, machine learning, and genomics, providing a strong foundation for interdisciplinary training. We
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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 and to