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PD Polarimetric Inference of Magnetic Fields 2026. PS-2026-007

Centro/Institution: 
Instituto de Astrofísica de Canarias
Tipo/type: 
Postdoctoral
País/Country: 
Spain
Fecha inicio solicitud: 
Vie, 13/02/2026
Fecha límite solicitud: 
Dom, 15/03/2026

Descripción/Description: 

The IAC (Tenerife) invites applications for ONE postdoctoral contract to work on the project linked to the line of research “Magnetism, polarization, and radiative transfer in Astrophysics”. The contract is funded by the project “Polarimetric Inference of Magnetic Fields” (PID2022-136563NB-I00), led by Dr. Tanausú del Pino Alemán and Prof. Javier Trujillo Bueno.

 

Research topics at the IAC include most areas of astrophysics: Solar Physics (FS), Exoplanetary System and Solar System (SEYSS), Stellar and Interstellar Physics (FEEI), The Milky Way and The Local Group (MWLG), Formation and Evolution of Galaxies (FYEG), and Cosmology and Astroparticles (CYA-CTA). All of these are supported by an ambitious instrumentation programme. Further information about the IAC's research programme, its Observatories and the 10.4m GTC is available at the IAC's web page: https://www.iac.es/en

 

Tasks:The successful candidate will pursue research in the following fields:

 

Spectro-polarimetric modeling and diagnostic of the upper solar atmosphere, including one or several of the following topics:

 

  • Theoretical investigations of the polarization in forbidden and permitted coronal lines.
  • Forward modeling of observations of the solar corona through the application of the group’s spectral synthesis codes (e.g., P-CORONA) in 3D models of the solar corona.
  • Testing and application of machine learning techniques to improve the study of the solar corona.
  • Spectro-polarimetric observations of chromospheric structures, and their analysis with the group’s Stokes-inversion codes (e.g., HAZEL, HanleRT-TIC, etc.).
  • Theoretical investigations of the polarization in chromospheric lines with the group’s spectral synthesis codes (e.g., HanleRT-TIC, PORTA, etc.).
  • Testing and application of machine learning techniques to improve the study of the solar chromosphere.

 

Particular attention will be given to applicants with experience in the field of spectro-polarimetry, atomic physics, radiative transfer, use of spectral synthesis and Stokes inversion codes.