Programa de Atracción y Retención de Talento Digital: "Enhancing the LHCb experiment at CERN wi[...]

Institut de Física Corpuscular; Paterna; Presencial; EUR 30.000 - 50.000; Jornada completa

Descripción de la vacante

A research institution in physics seeks MSc students for a 3-year contract focusing on enhancing data filtering systems at CERN using GPUs. Responsibilities include developing algorithms for particle reconstruction and optimizing energy usage through sustainable technology. Candidates should have a background in physics or computing science, with an interest in real-time processing and AI approaches.

Formación

• Aimed at MSc students in related fields.
• Experience or interest in data processing and AI/NN approaches is advantageous.

Responsabilidades

• Work on real-time data filtering and event selection system using GPUs.
• Support or develop components of algorithms for vertex finding and reconstruction.
• Contribute to energy optimisation and sustainability of the framework.

Conocimientos

Real-time data processing

High-performance computing

Experience with GPUs

Neural networks

Educación

MSc in physics, computing science, or similar subjects

Descripción del empleo

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.

Responsibilities

• 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.

Qualifications

• 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 details

Contract duration: 3 years

Keywords

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