I'm an undergrad in Computer Science looking for a research project in machine learning applied to phylogenomics, specifically reconstruction of phylogenetic trees. Currently, I'm working as a research intern at a Molecular Biology Lab automating bioinformatics pipelines. Basically, I try to facilitate the usage of exiting tools for my fellow biologists, but I want to go further. I would like to know how can I contribute to the development or optimization of techniques to generate/analyze phylogenies. Here is the reference website of the technique used here if you would like to take a brief look: https://www.ultraconserved.org/. TL;DR, you assemble a genome and align it to a set of probes to identify what is called ultraconserved elements (sequences that endure through evolution), from which it is possible to generate a phylogenetic tree, among other stuff. So. is it possible to use machine learning techniques to "predict" the location of biological markers? If so, what techniques should I explore? Do you have others ideas of applications of machine learning in phylogenomics? I tried to be brief, but I'm eager to know more. Hope we can develop some insights!