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research in computer science at the University of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete
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dispersal networks across Europe. The successful candidate will combine large-scale ecological datasets and species trait data, and use quantitative analyses to investigate how novelty of ecological networks
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functioning, and how this knowledge can be incorporated into biodiversity conservation. The doctoral researcher will focus on seed dispersal networks across Europe. The successful candidate will combine large
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approaches to large-scale biomedical data. Research topics may include foundation models for longitudinal electronic health records and genomics, multimodal learning integrating health records with molecular
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candidate is expected to develop an independent research programme within this broad scope, focusing on methodological innovation and the application of modern AI approaches to large-scale biomedical data
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in promoting or inhibiting sustainability transitions. The project focuses on large co-operatives in food, forestry, and retail sectors. Responsibilities and qualifications We are looking
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sex-specific natural selection effects at key life-history loci due to anthropogenic and environmental factors Use of long- term data on Teno salmon reproductive fitness to assess potential sex-specific