Single-Cell Population Genomics and Multi-omics Integration
Interns will apply machine learning techniques to integrate single-cell transcriptomic data with population-level genomic variation to understand cell-type-specific genetic effects. Projects include developing computational frameworks for linking genetic variants to cellular phenotypes using scRNA-seq and population genomics data.
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📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal
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