The high-luminosity conditions expected during Phase-II operations introduce significant challenges for object and event reconstruction algorithms planned for the EF, particularly for track reconstruction. The recent definition of the EF farm as a heterogeneous architecture combining CPUs and GPUs opens new opportunities for deploying machine learning models within the EF tracking workflow.

You will be part of the CERN ATLAS team and will contribute to research into the application of ML techniques for track reconstruction at the HL-LHC, with the goal of identifying and exploring the most promising approaches for deployment in the ATLAS EF tracking. The position is part of the Next Generation Trigger programme.

Be sure to meet the eligibility criteria

• By the application deadline, you have a master’s degree with 2 to 6 years of professional experience since graduation or a PhD with a maximum of 3 years of professional experience since graduation. You are not eligible with only a bachelor’s degree.
• You have never had a CERN fellow or graduate contract before.
• Please pay attention to the additional criteria and requirements for this specific position and mentioned above.