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incorporate it into mathematical models of trait evolution across phylogenies. The work combines dimensionality reduction and geometric data analysis with the development of statistically rigorous comparative
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variability. The work may include inverse problems, regularization strategies, statistical modeling, representation learning, and geometric or variational approaches to volumetric data. There is substantial
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to the development of novel tools for cancer risk assessment with real potential impact on healthcare. Qualifications Requirements A doctoral degree or an equivalent foreign degree in computer science, statistics
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well as collaborate with members of the team on research projects that fit their qualifications and interests. Primarly, the selected candidate will design and implement novel ML/statistical approaches dedicated
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the lab and bioinformatic/statistical analyses of next-generation sequence data. The project will be conducted in collaboration with Prof. Göran Arnqvist (Evolutionary Biology Centre, Uppsala University