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KTH Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health Project description Third-cycle subject: Medical Technology (Joint KTH-KI program) In
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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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science. We are looking for a candidate with a PhD in either engineering/computer science/physics/mathematics. Experience with ML implementation (ideally interpretable ML and/or generative AI) is required
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the development and use of complex model systems that enable the study of biological functions at the multicellular, cellular, and molecular levels under conditions resembling the body’s tissues or organs. This 6
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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