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. We develop machine learning methods tailored for high-dimensional, multimodal biological data, with applications ranging from single-cell genomics to real-world clinical datasets. We are active
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the benchmarking of continuum modeling code together with GTK. Take part in dissemination, outreach, and teaching activities. Profile of the candidate PhD in relevant field (Physics, Chemistry, Geology, Fluid
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, writing articles, supervising M.Sc and possibly PhD students as well as contributing to teaching in the Master's Programme in Particle Physics and Astrophysical Sciences. The candidate should have: A good
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microbiome from clinical patient samples Computational analysis and integration of functional microbial genomics datasets from next-generation sequencing methods. Supervision and teaching of students and
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, Greater Helsinki, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all