---------------------------------------------------------------------------------------------- Project: B6 Title: Analysis of boosted top quarks with CMS data using machine learning techniques DESY group: CMS Type: Online project Duration: 19th july - 10th sep 2021 Description: Tagging leptonically decaying boosted top quarks have not been much explored using jet image based techniques, as of yet. We would like to investigate the the use of Machine Learning techniques (like CNN and BDT) to tag leptonically decaying boosted top quarks in CMS. In addition, we also want to explore the use of such techniques to differentiate between left and right polarized top quarks. This can have very interesting implications for a variety of new physics models which can show up as deviations from the polarization expected from Standard Model processes. Special Qualifications expected: C++ and Python programming, ideally experience with Root; ideally some first experience with machine learning Link to further information: https://arxiv.org/abs/2010.11778 ----------------------------------------------------------------------------------------------