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the developmental rules underlying phenotypic variation. The successful postdoctoral fellow will develop and implement an empirical framework that utilizes data-driven algorithms to learn relationships between past
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bioinformatics, with a particular emphasis on performing analysis of high-dimensional data, which can be sequencing and/or imaging-based. Experience working with AI and machine learning approaches are considered a
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sequencing, and with computer scientists at KTH in Stockholm, focused on developing scalable probabilistic machine learning techniques for online phylogenomic analysis and placement of DNA barcodes. You will
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and is part of the National Program for Data-driven Life Science (DDLS ), generously funded by the Knut and Alice Wallenberg Foundation. Our research is focused on the use machine learning + AI tools as
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experience with machine learning techniques in general and neural networks in particular will be highly beneficial.
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and/or application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Tasks The tasks include primarily leading and conducting research
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use the data to train deep learning models of cancer. This allows us to identify systems-level mechanisms that can be used to uncover new biomarkers, drug targets, and paths to drug resistance. We
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and offers safe, favorable working conditions? We welcome you to apply for a postdoctoral position at Uppsala University. The research at the Department of Medical Biochemistry and Microbiology (IMBIM