Programa de Atracción y Retención de Talento Digital: "Enhancing LHCb experiment at CERN wi

Overview

Enhancing the LHCb experiment at CERN with sustainable technology

The LHCb collaboration at CERN is using a pioneering data filtering system in its trigger system based on real-time particle reconstruction using GPUs. The Allen project consists of over 365 algorithms that execute real-time vertex finding and reconstruction, fast-track particle reconstruction, calorimeter clustering, and muon identification with very high efficiency and throughput.

• Work on a real-time data filtering and event selection system that processes data with high throughput using GPUs.
• Support or develop components of Allen’s algorithms for vertex finding, reconstruction, fast-track reconstruction, calorimeter clustering, and muon identification.
• Utilize a fast and powerful neural network (NN) to suppress reconstructed objects from random detector hits and contribute to false trigger suppression.
• Develop tools to optimise energy usage and sustainability of the framework, including exploring hybrid computing platforms and efficient software solutions to increase physics output while reducing energy consumption.

• Aimed at MSc students in physics, computing science, or similar subjects.
• Experience or interest in real-time data processing, high-performance computing, GPUs, and AI/NN approaches is advantageous.

Contract duration: 3 years

• Artificial Intelligence (AI)
• Technologies for processing large amounts of data and information
• High-performance computing
• Green algorithms