1 Result(s)

Analysis of physics data using deep learning methods

Students can work on the following projects: 1. Novel approaches to simulation of nuclear track detector data for the MoEDAL experiment at the Large Hadron Collider using Generative Adversarial Networks 2. Position reconstruction of gamma and beta decays in the EXO-200 neutrinoless double-beta decay experiment using Convolutional Neural Networks Fluency in programming languages (Python and/or C, Linux OS) are required. Familiarity with deep learning technique and relevant software (PyTorch, Keras) are preferred. Access to GPU computing system will be provided...

Required Availability
The End of Time
Course Credit?
Yes - PH495
Paid Position?