In recent years, the amount of data collected in the ATLAS experiment at the Large Hadron Collider has doubled. At the same time, computational methods and machine learning methods have also advanced rapidly, enabling the use of the latest technologies to analyse this large amount of data.
The doctoral candidate will focus on analysing data from the latest two measurement periods at the Large Hadron Collider. For the analysis of the large amount of experimental data they will use machine learning and simulation methods to optimise search strategies. The specific physics process, that will be the focus of the analysis, will be determined in consultation with the candidate.
The work will take place in a highly international environment in collaboration with more than 3,000 scientists. Multiple visits to the CERN laboratory are also planned.
Dr. Tadej Novak
Dr. Tadej Novak is a researcher at the Experimental Particle Physics Department – F9, where he participates in the ATLAS experiment at the Large Hadron Collider at CERN in Geneva. He focuses on data analysis and developing new methods for detector simulations. He places great emphasis on the use of machine learning to improve the accuracy and speed of research methods.
Research programme: Experimental elemenetary particle physics
Training topic: Machine learning assisted data analysis at the ATLAS experiment