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Are you passionate about applying computational approaches to solve problems within chemistry and biology? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a
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will combine state-of-the-art computer vision, modeling and archived specimens to determine biotic and abiotic factors driving spatial variation in molt phenology. It will use museum genomics to recover
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precision medicine. We are situated at the Science for Life Laboratory (SciLifeLab) and this position is part of the Data Driven Life Science program (DDLS). Assistant professor Avlant Nilsson will be
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will be expanded with the recruitment of 19 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School