Offre en lien avec l’Action/le Réseau : – — –/– — –
Laboratoire/Entreprise : Laboratoire d’Etudes Spatiales et d’Instrumentatio
Durée : 3 à 6 mois (négociab
Contact : anne-marie.lagrange@obspm.fr
Date limite de publication : 2021-02-15
Contexte :
Recent studies have demonstrated that coupling high contrast imaging with medium or high resolution spectroscopy leads to a significant improvement in the detection capability of exoplanets, in particular young ones, and to constrain their physical and chemical properties (Hoejmakers et al, 2018, https://arxiv.org/pdf/1802.09721.pdf). This technique, called Molecule Mapping exploits the diversity contained in the data and could on the long term allow to detect and characterize Earth twins around other stars.
Sujet :
The Internship will be devoted to the analysis of a sample of young stars surrounded by transition disks, using data collected at the with the spectro-imager SINFONI mounted on the ESO Very Large Telescope (Chili). These stars, aged a few million years are surrounded by dust disks called transition disks that have been resolved by high contrast imagers at the VLT and/or by the ALMA radio interferometer. An example is PDS70 (Keppler et al, 2018, https://arxiv.org/abs/1806.11568), in which two planets have been detected in the central cavity of a dust transition disk.
The intern will use existing algorithms developed in Grenoble and Paris to analyse the data. if necessary, (s)he will further develop these algorithms. (S)he will interpret the results obtained for each individual system.
The intern will be supervised by Anne-Marie LAGRANGE and Anthony BOCCALETTI at LESIA (Paris) and remotely by Mickaël BONNEFOY at IPAG (Grenoble).
S)he will be a member of the ERC COBREX, collaborating with researchers from the Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique (Obs. de Paris), the Institut de Planétologie et d’Astrophysique de Grenoble (IPAG) and the Centre de Recherche Astrophysique de Lyon (CRAL).
Profil du candidat :
The intern should demonstrate her/his ability to work in Python and have solid grounds in signal processing.
Formation et compétences requises :
Excellent knowledge of Python and the following libraries (numpy, scipy, pandas, scikit-learn).
Adresse d’emploi :
LESIA
Observatoire de Paris, Section de Meudon
5, place Jules Janssen
92195 MEUDON Cedex