Data driven study of spectroscopic archives using deep neural networks

In this project we will apply deep learning techniques on spectroscopic data and seek to study the potential physical representations the networks learn.
Please take a look at a recent sample work on https://www.eso.org/~nsedagha/universe/ to familiarize yourself with the general idea.

Prior experience with CNN training workflows using Pytorch is a must.