Machine learning for axion dark matter data analysis
Chiara Salemi, Professor
Physics
Applications for Fall 2025 are closed for this project.
Axions are a highly motivated candidate to be the dark matter. The signal profile in a detector depends on the properties of the Milky Way's dark matter halo properties. Certain halo models predict signal shapes that are challenging to differentiate from noise, and recent work has indicated that machine learning-based analysis techniques may benefit signal-to-noise discrimination.
Qualifications: Your role is to assist in the writing and testing of machine learning algorithms with simulated and real axion experiment data.
Required qualifications: good communication skills, ability to work well in teams, careful attention to detail, some coding experience
Desired but not required qualifications: experience with machine learning, experience with python
Hours: 9-11 hrs
Related website: https://