Moises Barbera Ramos graduated with honours from the University of Liverpool (UoL) with a master’s in physics, specialising on applying computational methods to solve physics problems.
He worked at CERN for 4 months during summer 2019, developing a several-thousand-lines-long algorithm that automatically studied the trajectory of billions of particles moving from the SPS to the LHC. As a result, this study presents potential sources causing the instability of transfer lines TI2/TI8 during RUN II (view study here).
Moises’ Master’s thesis was developed for the selective FASER collaboration (CERN). He recognised and simulated the expected trajectories of Dark Matter indicators generated from collisions at ATLAS and studied the response of the calorimeter detector used by this collaboration. His results are been used on the construction of a new 2 million dollar particle detector, bringing science a step closer to detecting Dark Matter.
Outside academia, Moises used his technical skills at JP Morgan and Chase to develop algorithmic trading strategies and as the Vice-President of the Coding and Robotics Society where he developed a new hand tracking algorithm applied to remote car driving, winning the robotics competition award at the XJTLU University in Suzhou, China.
His experience and enthusiasm to contributing to science and solving complex problems made him the first hire of the NOVAS collaboration, been part of this exciting team since the beginning.