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H/F PhD position on deep learning cosmic shear

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

Date Limite Candidature : mardi 29 novembre 2022

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General information

Reference : UMR7326-ANAMEK-054
Workplace : MARSEILLE 13
Date of publication : Tuesday, October 18, 2022
Scientific Responsible name : Nicolas Martinet & Stéphane Arnouts
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2023
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly

Description of the thesis topic

We are opening a doctoral position at the Laboratoire d'Astrophysique de Marseille (LAM) to work on the development of deep learning techniques for cosmic shear analyses. This three-year position is part of the PISCO (PIxelS to COsmology) grant funded by the Agence Nationale de la Recherche (ANR). The selected PhD candidate will mainly focus on measuring the gravitational distortion of galaxy shapes (called the shear) directly from galaxy images, using convolutional neural networks (CNN). He/she wil develop the galaxy image simulation and CNN architecture with the goal of applying these techniques to the Euclid satellite that should be launched at the beginning of the thesis.

Work Context

The successful candidate will join the Galaxy and Cosmology (GECO) team at the LAM and work closely with Nicolas Martinet and Stéphane Arnouts. He/She should also join the Euclid Consortium and collaborate with the Organizational Unit SHEar for the image simulation and shear calibration tasks. The LAM is one of the largest astrophysics laboratories in France with a dynamic international environment. It also benefits from the ideal location of Marseille, the 2nd largest city in France, sunny, and on the Mediterranean Sea.

Constraints and risks

Possible national and international travels.

Additional Information

The starting date is scheduled on the 1st of October 2023 but is flexible.
A master internship is also possible in 2023 as a first step to the thesis, but not required.
Applicants should submit a CV, their master grades, and a one-page cover letter on the CNRS portal and should arrange for one letter of recommendation to be sent to Nicolas Martinet by email (nicolas.martinet@lam.fr) by the closing date (December 5). Please contact Nicolas Martinet by email (nicolas.martinet@lam.fr) for any question relative to this job offer.

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