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Portal > Offres > Offre UMR7326-FRELEP-044 - H/F Position postdoctorale en deep learning appliqué aux redshifts photométriques

H/F Postdoctoral position in deep learning for photometric redshifts

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

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General information

Reference : UMR7326-FRELEP-044
Workplace : MARSEILLE 13
Date of publication : Wednesday, January 29, 2020
Type of Contract : FTC Scientist
Contract Period : 24 months
Expected date of employment : 1 April 2020
Proportion of work : Full time
Remuneration : between 2695 et 4291 monthly gross according to experience
Desired level of education : PhD
Experience required : Indifferent


Applications are invited for a postdoctoral position in the Laboratoire d'Astrophysique de Marseille (LAM), France. The candidate will work on developing deep learning methods for photometric redshift estimates with large imaging surveys.


The candidate is expected to develop new deep learning techniques, in particular to handle the unbalanced and incomplete representativity of the spectroscopic training sets currently plaguing machine learning methods. S/he will have the opportunity to participate in and initiate scientific analyses using the resulting millions of photometric redshifts estimated on current large imaging surveys (CFHTLS, KIDS, HSC, …). S/he will also be encouraged to extend the methods to the measurements of galaxy physical properties and confront them with different SED-fitting and machine learning approaches. Such work will be a stepping stone to the LSST survey.


Experience in machine learning or deep learning will be preferred

Work Context

The position is funded by the French National Research Agency for the project “DEEPDIP”. This project is a collaboration between CCPM (Marseille), TETIS (Montpellier) and IAP (Paris) with expertise in deep learning.

LAM has an animated research atmosphere in various fields of astrophysics. Marseille is a Mediterranean harbor with a colorful ambience and a diverse cultural mix.

Additional Information

Applicants should send their CV with a research summary and a letter of interest for the position as well as three reference letters.

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