I joined the Computer Simulation in Science (CSiS) program at the University of Wuppertal after a Bachelor in Physics with a minor in computer science at Birzeit University in Palestine. I chose this master program because I was interested in learning experimental techniques to study physics phenomena. The CSiS program offers a mixture of mathematics, computer science and natural sciences with the focus on computer simulation to solve problems in natural sciences. During my CSiS studies, I enjoyed the lab courses the most, where I learned how to implement mathematical models such as, the Ising model, the Runge-Kutta methods and the Monte Carlo methods. I also learned how to parallelise my code and optimise it to run more efficiently. I gained knowledge from every course and practical exercise in the CSiS program, in particular, courses in data analysis, computer simulation, parallel programming and GRID computing. I also appreciated a lot the environment at the University of Wuppertal and the support of the professors and lecturers of the CSiS program. I chose the specialisation in experimental particle physics, where I carried out my master thesis in the analysis of data generated in a proton-proton collision at the Large Hadron Collider (LHC) and collected by the ATLAS detector. My master thesis was performed under the supervision of Prof. Dr. Peter Mättig and included studies on a new method to model the W-boson production in association with jets (W+jets) background process for the top-quark pair production process with the ATLAS experiment. This method models the W+jets process using Z+jets events in a data-driven approach.

After finishing my master studies, I pursued my doctoral studies with the same group and supervision as for my master thesis. The method developed during my master thesis was used and published during my doctoral work. My PhD topic is a measurement of the inclusive and fiducial top-quark pair production cross-sections in the lepton+jets channel at a centre-of-mass energy of 8 TeV with the ATLAS detector. The measurement was performed by separating the selected events into three disjoint regions and training of a neural network to improve the separation between the signal and the backgrounds. The neural network output distribution was used as a discriminant in two signal regions while the mass of the hadronically decaying top-quark was used in the third one. This configuration improved the sensitivity to systematic uncertainties affecting the measurement. A simultaneous binned maximum-likelihood fit was performed in the three regions to determine the top-quark pair production cross-section. This measurement is the most precise measurement in this channel by the ATLAS collaboration with a precision of 5.7% for the inclusive cross-section. My dissertation can be found here: http://elpub.bib.uni-wuppertal.de/servlets/DerivateServlet/Derivate-8595/dc1902.pdf

After finishing my doctoral studies, I am currently working as a postdoctoral researcher at Paderborn University in the data science group (DICE). Participating in the CSiS program paved the path for my research career and was an exceptional experience for me, I highly recommend it.

26.11.2019