Machine Learning Classification of Short Gamma-Ray Transients

Project Description:

This Honours project applies machine learning techniques to classify short gamma-ray bursts (SGRBs) and magnetar giant flares (MGFs), which are difficult to distinguish due to their similar temporal and spectral features. Using an existing Fermi-GBM dataset, the student will perform exploratory data analysis, apply dimensionality reduction via PCA, and evaluate classifiers such as Random Forests and k-Nearest Neighbours to determine which physical parameters best separate the two transient classes. For full details, please refer to the attached project proposal.

Research Area:

Astrophysics

Project Level:

Honours

This Project Is Offered At The Following Node(s):

(NWU)

Special Requirements:

Students should have basic level of python.