Deep Learning Models for Metagenomic Sequence Assembly

Metagenomics › Machine Learning Metagenome Assembly Research

Deep Learning Models for Metagenomic Sequence Assembly

Interns will develop and optimize neural network architectures (CNNs, RNNs, Transformers) for predicting overlaps between metagenomic reads and improving contig assembly quality. They will work with real sequencing datasets to train models that outperform traditional graph-based assembly algorithms in handling complex microbial communities.

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