Ref. 6286_All. 3 - High Energy Physics with the ATLAS experiment at the Large Hadron Collider

Italian Ministry of Education, University and Research

Italia

In loco

EUR 36.000 - 48.000

Tempo pieno

2 giorni fa
Candidati tra i primi

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Il tuo curriculum e una lettera di presentazione personalizzati, che corrispondono esattamente a ciò che sta cercando.

Supera i filtri ATS

Descrizione del lavoro

The Alma Mater Studiorum - University of Bologna, Department DIFA - Physics and Astronomy, seeks a leading researcher to contribute to the ATLAS experiment at CERN, performing data analysis, software development and participation in working groups.

The project focuses on advanced computing techniques including deep learning, and includes detector-related tasks and involvement in phase 2 upgrade subsystems.

Competenze

  • Participation in experimental activities, data analysis and software development at the ATLAS experiment of the LHC at CERN.
  • Involvement in working groups with reference to analysis and advanced computing techniques also based on deep learning.
  • Technical activities related to the detector, including subsystems designed for the phase 2 upgrade.

Descrizione del lavoro

Organisation/Company Alma Mater Studiorum - Universita' di Bologna Department DIFA - Dipartimento di Fisica e Astronomia Research Field Physics » Other Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 3 Dec 2026 - 23:59 (UTC) Country Italy Type of Contract Temporary Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The research project includes participation in experimental activities, data analysis and software development at the ATLAS experiment of the LHC at CERN. The project includes involvement in working groups, with reference to analysis and advanced computing techniques also based on deep learning. Furthermore, technical activities related to the detector are also foreseen, including the subsystems designed for the phase 2 upgrade

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