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patterns from noisy and censored data, or c) developing methods to analyze effects of extreme climate events on species communities. The candidate is also expected to contribute to other projects within
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models (JSDM) to analyze ecosystem functions provided by species communities, b) developing methods to infer species and community level phenological patterns from noisy and censored data, or c) developing
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microbes, and water bodies are featured in existing discourses, representations, and imaginaries of algal blooms; b) design and conduct an independent ethnography that examines the expanding more-than-human
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, I. and Shimmi, O. (2022). Mechano-chemical feedback mediated competition for BMP signalling leads to pattern formation. Dev Biol. 481:43-51. https://doi.org/10.1016/j.ydbio.2021.09.0063 . Gui, J
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conduct field manual sampling campaigns (e.g stable isotope labelling, soil water sampling) and associated sample analyses in the laboratory; In addition, the successful candidate should be able to: Design
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responsibilities Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data Collaborate closely with
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Helsinki GSE , an expanding and international economics research unit. The Centre studies the effects and design of tax-benefit policy and regulation and focuses on providing new credible evidence on
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morphology imaging, and spatial transcriptomics—to identify altered cell states and mis-patterning events. The aim is to integrate computational and experimental approaches, including validation in vivo