Project to be confirmed after rotation year

点击翻译按钮获取中文摘要

Inferring how recent adaptation shaped genomic architecture is crucial tounderstanding the molecular mechanisms underpinning diversity among species andgenetic variation within populations. The recent rise of artificial intelligence hascreated new opportunities in this area. Novel approaches based on deep learning areshowing great promise, especially for scenarios where existing methods are lackingpower. This project will build on recent advances in the field to further develop deeplearning algorithms to infer adaptive evolution from large-scale genomic data and testthem on data from wild populations and controlled evolve-and-resequenceexperiments in Drosophila melanogaster.