Missions

Deep convection plays a central role in the functioning of the global climate system. It is a key driver of intense rainfall events and contributes to the vertical transport of heat, moisture, and energy in the atmosphere, particularly through the high-level clouds it generates. These processes are organized into large-scale convective systems (e.g., mesoscale convective systems), which are observable from space.
Despite scientific progress, these systems remain poorly represented in climate models, especially in the context of global climate change.
The recruited research engineer will provide technical and methodological support to the team's scientific work on deep convection. The engineer will contribute in particular to the analysis of convective systems using satellite observations.
This work is part of a broader international scientific effort, involving the development of high-resolution climate models (e.g., Digital Twin Earth, DestinE) and the preparation of upcoming satellite missions, such as AOS/C2OMODO and WIVERN, which will provide unprecedented observations of convective systems in the next decade.

Activités

In this context, the research engineer will contribute to the scientific projects of the EMC2 team, focusing particularly on the most active regions of convective systems, where intense vertical motion and heavy precipitation are concentrated.
Main activities will include:
- Developing, optimizing, and maintaining a Level 4 data fusion algorithm that integrates multiple sources of satellite observations, including infrared imagery from geostationary satellites and vertical radar profiles from low Earth orbit missions such as TRMM, GPM, CloudSat, and EarthCARE.
- Designing structured, consistent datasets ready for use in machine learning and artificial intelligence workflows;
- Taking ownership of existing in-house tools used for analyzing storm structure and organization: maintenance, adaptation, and optimization;
- Contributing to deep learning developments, in particular using convolutional neural networks (CNNs) to enrich the representation of convective systems based on radar data;
- Ensuring rigorous version control (Git), clear and sustainable documentation, and contributing to the wider dissemination of tools within the research community.

Compétences

- Engineering degree or PhD in Environmental or Earth Sciences, with experience in scientific computing and image processing;
- Excellent skills in scientific programming (Python, C; IDL appreciated) and experience with version control systems (Git);
- Good working knowledge of Linux environments;
- Experience handling large-scale datasets and applying statistical methods (satellite data experience is a plus);
- Experience with machine learning techniques;
- Strong attention to detail and rigor in technical documentation; ability to maintain and structure shared research tools;
- Good communication skills, both written and spoken;
- Proficiency in English (written and oral) at B2 to C2 level;
- Autonomy, strong interpersonal skills, and ability to work effectively in a team.

Contexte de travail

The position will be hosted at LEGOS (Laboratory for Geophysical and Oceanographic Studies), located on the Observatoire Midi-Pyrénées campus in Toulouse, France. LEGOS includes approximately 130 staff members and conducts cutting-edge research in oceanography, climate science, and satellite remote sensing.
The recruited engineer will join the EMC2 team, which focuses on understanding variations in the global water and energy cycle in response to ongoing climate change. The engineer will benefit from a dynamic national and international research environment and will collaborate closely with researchers, engineers, and PhD students in the team.