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annotating experimental findings from the literature— with advanced machine learning approaches to extend functional annotation of LCRs. • Apply clustering algorithms to group LCRs by similar annotation
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the project is the development of AI-based pipelines for detecting, segmenting, and classifying lichen communities. Convolutional neural networks (e.g., U-Net, DeepLab) and machine-learning algorithms (e.g
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of biological databases, algorithms and pipelines; experience in working with phylogenetic/ genomic/transcriptomic/systems biology tools will be a bonus; being well organized, eager to learn and ready to
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environments within NWLs. The results will provide insights into the genetic and evolutionary relationships between species, the functional elements of genomes, and the mechanisms driving genomic diversity and