25 Feb 2025
Job Information
- Organisation/Company
CNRS- Department
Laboratoire d'Instrumentation et de Recherche en Astrophysique- Research Field
Astronomy
Astronomy » Astrophysics
Astronomy » Cosmology- Researcher Profile
First Stage Researcher (R1)- Country
France- Application Deadline
17 Mar 2025 - 23:59 (UTC)- Type of Contract
Temporary- Job Status
Full-time- Hours Per Week
35- Offer Starting Date
1 Jul 2025- Is the job funded through the EU Research Framework Programme?
Not funded by a EU programme- Is the Job related to staff position within a Research Infrastructure?
No
Offer Description
This position will consist of using "deep learning" methods, in particular CNNs and "transformers" for the processing of data from the IASI instrument from CNES. These observations are brightness temperature measurements observed by the IASI instrument in orbit, a spectrum of more than 8000 channels gives information at several wavelengths in the infrared, to estimate environmental variables such as atmospheric temperature and water vapor profiles, or surface temperature. We search for the solution of an inverse problem, and we want to use a neural network model for this task. Our group has been using this type of method for 30 years, the aim here is to experiment with recent techniques, which will be able to exploit spatial patterns, manage missing data, and estimate uncertainties
This type of work is always characterized by the same steps:
1. Understanding and construction of heavy and complex databases, of various origins, which must be co-located and projected on a common grid.
2. Tests of various models must then be done, with the definition of metrics to diagnose their quality. We are moving here towards deep learning methods, based on significant experience in the group, but exploring the most efficient recent methods. A critical eye, a perfect mastery of the tools to develop particular models yourself, are necessary for this work.
3. Analysis of the results is then continued to quantify errors, analyze the pros/cons of each model, and possibly use this knowledge to iterate on model development.
4. A reporting phase is then necessary, to make presentation materials, write a report and a scientific article (English required)
This work is funded by CNES, as part of support for laboratories to develop next-generation satellite data processing algorithms. New space missions are coming (IASI-NG, MSG third generation) and we need to develop innovative and efficient methods capable of processing an increasingly large mass of data, which is increasingly complex.
The post-doc will work under the responsibility of Filipe AIRES, and Catherine Prigent, in the "Planetology" department of LIRA. He will be surrounded by several researchers/PhD students who work in the field of satellite remote sensing. The work will be carried out on the Paris site of the Paris Observatory.
Where to apply
- Website
- https://emploi.cnrs.fr/Candidat/Offre/UMR8254-SYLDES-005/Candidater.aspx
Requirements
- Research Field
- Astronomy
- Education Level
- PhD or equivalent
- Research Field
- Astronomy
- Education Level
- PhD or equivalent
- Research Field
- Astronomy
- Education Level
- PhD or equivalent
- Languages
- FRENCH
- Level
- Basic
- Research Field
- Astronomy
- Years of Research Experience
- None
- Research Field
- Astronomy » Astrophysics
- Years of Research Experience
- None
- Research Field
- Astronomy » Cosmology
- Years of Research Experience
- None
Additional Information
Eligibility criteria
The reauired skills are:
1. A very good level in programming, Matlab and Python
2. A very good command of satellite data, in remote sensing, in geosciences
3. A mastery of applied mathematics tools, particularly in statistics and machine learning
- Website for additional job details
https://emploi.cnrs.fr/Offres/CDD/UMR8254-SYLDES-005/Default.aspx
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- Laboratoire d'Instrumentation et de Recherche en Astrophysique
- Country
- France
- City
- PARIS 14
- Geofield
Contact
- City
PARIS 14
STATUS: EXPIRED
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