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Portail > Offres > Offre UMR7585-ABIJOR-001 - Intitulé de l'offre : Post-Doc groupe ATLAS au LPNHE (H/F) - CDD 24 mois

Post-Doc in the LPNHE ATLAS groupe (M/W) - CDD 24 mois Workplace : PARIS 05

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

Date Limite Candidature : mardi 1 février 2022

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General information

Reference : UMR7585-ABIJOR-001
Workplace : PARIS 05
Date of publication : Tuesday, January 11, 2022
Type of Contract : FTC Scientist
Contract Period : 24 months
Expected date of employment : 1 February 2022
Proportion of work : Full time
Remuneration : 2743-3161€ gross monthly depending on experience
Desired level of education : PhD
Experience required : Indifferent

Missions

This post-doc offer proposes to work on the search for axion-like particles (PTA) decaying into photon pairs that may have a very short lifetime or, on the contrary, be long enough to allow decay within the ATLAS calorimeters. This offer is part of the DMwithLLPAtLHC project, carried by two teams of experimentalists involved in the ATLAS experiment (LPNHE Paris and LPSC Grenoble) and a team of phenomenologists from LPTHE Paris, supported by the ANR.

Activities

The selection of such events can benefit from an approach using machine learning algorithms in several ways: regressions to improve the measurement of the energy and direction of electromagnetic sprays or classifications to distinguish single or double sprays that can appear in the case of boosted photon pairs. From a theoretical point of view, successfully relating the time of flight and production rate of a PTA to the parameters of a model is a non-trivial task. In addition to the development of the analysis, the hired individual will work with the LPTHE theory team to ensure that the analysis is constructed in a way that makes it as easy as possible to reinterpret the measurement in another theoretical framework.

Skills

Mastery of data analysis in the ATLAS experiment (ATLAS qualified author), mastery of the usual particle physics concepts, mastery of C++ and python languages. Experience with TensorFlow and Pytorch libraries will be appreciated.

Work Context

The LPNHE is a joint research unit of 160 people whose research is mainly experimental in particle physics and astroparticles.

Additional Information

PhD in particle physics required. A use of machine learning tools in a research context will be considered as a positive element of the file.

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