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Portail > Offres > Offre UMR5033-JANSTA-003 - Post-doctorant sur les méthodes d'apprentissage profond pour la reconstruction et l'analyse des données de l'expérience ATLAS auprès du LHC (H/F)

Post-doctoral researcher on deep learning methods for the reconstruction and analysis of data from the ATLAS experiment at the LHC (M/W)

This offer is available in the following languages:
- Français-- Anglais

Date Limite Candidature : dimanche 10 décembre 2023

Assurez-vous que votre profil candidat soit correctement renseigné avant de postuler

Informations générales

Intitulé de l'offre : Post-doctoral researcher on deep learning methods for the reconstruction and analysis of data from the ATLAS experiment at the LHC (M/W) (H/F)
Référence : UMR5033-JANSTA-003
Nombre de Postes : 1
Lieu de travail : TOULOUSE
Date de publication : vendredi 27 octobre 2023
Type de contrat : CDD Scientifique
Durée du contrat : 24 mois
Date d'embauche prévue : 1 décembre 2023
Quotité de travail : Temps complet
Rémunération : between €2905 and €4081 gross per month, depending on experience
Niveau d'études souhaité : Niveau 8 - (Doctorat)
Expérience souhaitée : 1 à 4 années
Section(s) CN : Interactions, particles, nuclei, from laboratory to cosmos

Missions

The Particle Physics team at the Laboratoire des 2 Infinis - Toulouse (L2IT) is offering a post-doctoral contract to reinforce its activities on the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. The successful candidate will work at L2IT. His or her work will focus on the development of deep learning methods for the reconstruction and/or the analysis of data from the ATLAS experiment.

Activités

The successful candidate will develop innovative analysis methods for the reconstruction or the analysis of data from the ATLAS experiment. The L2IT team plays a leading role within the ATLAS collaboration in the reconstruction of charged particle tracks using deep geometric learning (GDL). The person joining us can contribute to this effort, for example by applying GDL to signatures not considered in the existing studies (electrons or tracks produced far away from the centre of the detector). Other applications of machine learning for the reconstruction or the analysis of ATLAS data are possible, depending on the candidate's experience and motivation.

Compétences

We are looking for a colleague with a PhD in particle physics or in computer science with a strong specialisation in machine learning, with a PhD degree obtained less than three years before the start date at L2IT. Proven experience with machine learning to solve a scientific problem, or experience with algorithms for particle physics would be a plus.

Contexte de travail

The Laboratoire des 2 Infinis - Toulouse (L2IT) is a laboratory created in 2020 to conduct research in fundamental physics with new numerical and theoretical approaches to data analysis. The laboratory's research focuses on particle physics, gravitational waves and the equation of state of nuclear matter, and is supported by the concurrent development of data science and analysis methodologies. L2IT is operated by CNRS/IN2P3 and Université Toulouse III - Paul Sabatier. The L2IT Particle Physics team contributes to understanding the dynamics of the scalar sector of the Standard Model through studies of the Higgs boson and of the polarisation of vector bosons. It contributes to the development of data reconstruction software for the new tracker (ITk) that the ATLAS collaboration will install for the high-luminosity phase of the LHC. The successful candidate will work in close collaboration with other members of the Particle Physics team, and with members of the Computing, Algorithms and Data team at L2IT.

Contraintes et risques

Short trips in France and abroad are required.