27 evolution "https:" "https:" "https:" "Multiple" research jobs at University of Oslo
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The successful candidate will study diversity at multiple taxonomic levels in space and time of selected
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models for high-dimensional and functional data ”, led by Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available
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at multiple taxonomic levels in space and time of selected groups within the petaloid monocots. The candidate will use an integrative approach to these studies, using a molecular phylogenetic framework to study
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on the development of bioinformatic tools and advanced omics- and biomarker analyses. Highly motivated candidates with strong analytical skills will have excellent opportunities to contribute to multiple high-impact
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related to models and multiple sources of data describing ecological dynamics. The PhD project will address the following aims: 1) Develop efficient tools for learning about models from data, 2
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Work . The successful candidate will study diversity at multiple taxonomic levels in space and time of selected groups within the petaloid monocots. The candidate will use an integrative approach
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Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of dynamic sequential inference
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-dimensional and functional data ”, led by Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to
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communication skills in English English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html
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falls short: multiple biologically plausible definitions of “true” clusters coexist, analyses typically rely on a single dataset and potentially misleading validation metrics, and robustness is seldom