Applications of machine learning to Higgs physics
Research Group:Particle Physics Research Centre
Length of Study in Years: 3.4
Full-time Project: yes
The Higgs boson is central to our understanding of the Standard Model. This project is focussed on the study of this particle and in particular the search for for H decays into pairs of b quarks using data from the LHC experiment at ATLAS. This project will also involve exploring the application of modern machine learning algorithms to this problem; with the aim to improve our understanding of fundamental physics. Machine learning areas of interest include Neural Networks, Decision Trees, Support Vector Machines, Deep Learning and generalisation.
There are opportunities to spend one year in Geneva during the course of their PhD, while this is not mandatory it is strongly encouraged. Some grasp of C++ and statistics is desirable.
SPA Academics: Adrian Bevan, Seth Zenz