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project, SmartWheat: Harnessing AI Models for Climate-Resilient Wheat Varieties in Sustainable Agriculture, at NMBU. The successful candidate will develop AI-driven models for the analysis of UAV-based
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with taxonomic expertise, quantitative ecology, and spatial modelling, the project aims to: Characterize the ecosystem functions of coastal cold-water coral (CWC) and sponge habitats, and assess how
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candidate will help design, implement, and evaluate a novel science-policy engagement process that combines climate modeling, role-play simulations, future storytelling, and participatory workshops
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of the following: computational analysis of human movement and/or vocalization, time series analysis, pattern finding, statistical modelling, audio feature extraction, music information retrieval, machine learning
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-cell RNA-seq, multiOme-seq (RNA+ATAC) and spatial transcriptomics (Visium HD, Xenium) and spatial epigenomics. We utilize a wide range of cell-based models, organoid systems and patient material together
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of the following: computational analysis of human movement and/or vocalization, time series analysis, pattern finding, statistical modelling, audio feature extraction, music information retrieval, machine learning