One of the important aspects of searches for new physics at the Large Hadron Collider (LHC) involves the identification and reconstruction of single particles, jets and event topologies of interest in collision events. In order to correctly reconstruct particles of interest, high resolution is required.
This project will focus on developing machine learning models to map processed, lower resolution data from particle from simulated particle collisions back to a higher resolution representation.
Total project length: 175/350 hours.
Python, C++, and some previous experience in Machine Learning.
Please DO NOT contact mentors directly by email. Questions should instead be directed to ml4-sci@cern.ch which is forwarded to mentors. To submit your proposal, CV, and test task solutions, please use this Google form.