Master positions
Master 2 internship - Analysis of Perseverance rover data
SUMMARY
InstitutionUniversité Grenoble-Alpes
DepartmentIPAG
LocationGrenoble, France
Work arrangementin person
Duration5-6 months, flexible
Salary~660€/month
Number of positions1
Application deadline2026-12-21
Start date2027, flexible
Posted2026-09-25
Posted by0000-0002-9310-0742
JOB DESCRIPTION
- Laboratory: IPAG
- Advisors: Dr. Lucia Mandon; Prof. P. Beck
- Contact: lucia.mandon[at]univ-grenoble-alpes.fr; pierre.beck[at]univ-grenoble-alpes.fr
- Location: IPAG PhITEM D, 122 rue de la piscine, 38400 Gières
- Desired candidate profile: candidate in a Master’s degree in Earth Sciences and/or Planetary Sciences
- Keywords: planetary science; Mars; rover; spectroscopy
Context
Martian dust is rich in iron oxides and responsible for the planet’s characteristic orange color over much of its surface. This thin layer interferes with the interpretation of spectral observations obtained from orbit, which are the main sources of information on the composition of Martian surface rocks and, therefore, on the geological history of the planet. To correct its contribution, it is crucial to accurately characterize the spectral signature of the dust, particularly in reflectance, which is the primary technique used from orbit for mineralogy. Since 2021, the Perseverance rover has been exploring an ancient dry lake on the surface of Mars to investigate its past environments and habitability. Using the Franco-American SuperCam instrument, Perseverance provides a unique opportunity to study the spectral signature of dust through the observation of dusty targets (e.g., rocks or even the rover itself).
Internship objectives
The intern will take advantage of Perseverance’s wealth of public data to 1) identify and select dusty targets from images and spectra acquired by SuperCam, 2) identify the spectral characteristics (visible and near-infrared) of Martian dust, 3) apply separation methods (e.g., ICA (algorithms provided)) to isolate the specific contribution of dust in spectral measurements.
Tools
Data analysis tools (e.g., Python)
Apply
To apply, please send a CV (including the previous research internship(s) and name of supervisors), and a copy of master grades at lucia.mandon[at]univ-grenoble-alpes.fr and pierre.beck[at]univ-grenoble-alpes.fr.