736 English-speaking jobs in Occitania

Develop a machine learning model to predict the in-flight response of a multi-head particle detector based on ground calibration data. The model will account for instrumental effects and background noise, enabling systematic calibration and intercalibration between detectors.

This PhD analyzes the dynamics of internal tides (ITs), focusing on high modes and solitons, and their interactions with mesoscale circulation. The goal is to develop an AI-based method for automatic IT detection in SWOT and ocean color data to improve chlorophyll mapping.

This PhD study investigates the impact of high-energy radiation on spacecraft components and characterizes electrostatic discharges on critical elements. The research involves experimental, instrumental, and numerical methods to identify and measure discharges under simulated space conditions.

This thesis develops a probabilistic framework for collision risk assessment in space, addressing uncertainties in covariance matrices, Time of Closest Approach, and nonlinear dynamics.

This thesis focuses on improving numerical simulations of gas flows in hybrid rocket engine combustion chambers. The work involves integrating a pyrolysis law for solid fuel degradation into the MoDeTheC code and coupling it with the CEDRE code to simulate mass and heat transfer at the fluid/fuel interface. Simulations will be validated against experimental data from ONERA and used to optimize combustion chamber geometries for improved engine performance.

This PhD research will investigate the microphysics of triboelectric charging of dust grains on Mars. The study will combine experimental, theoretical, and numerical approaches to understand how charge is exchanged during grain-grain collisions and how ambient conditions influence these exchanges. Results will be compared with in situ data from the SuperCam instrument on the Perseverance rover.

This project aims to design a next-generation attitude simulator testbed capable of assessing attitude control algorithms under realistic conditions. The new design will eliminate disturbances not found in orbit and handle active dynamic imbalances at the payload level. The project will investigate the use of miniaturised Control Moment Gyroscopes (CMGs) for agile balancing algorithms, decoupling an agile balancing system from the payload's ADCS, and optimizing nonlinear multibody simulations for prototyping and validating control algorithms.

This research explores the potential of silicon-based front-end circuits operating at 183 GHz and 325 GHz for miniaturized space radiometers. The study aims to address challenges such as lower electron mobility and substrate losses in silicon technologies compared to III-V semiconductors.

This PhD research develops robust models of four-wheeled rovers for dynamic behavior, aiming to increase cruising speed to five meters per second. The research integrates structural characteristics, damping, control, and interface capabilities with emerging technologies.

This thesis focuses on developing a reduced-order model for the Salammbô 3D electrons code, used to simulate Earth's radiation belts. The research will explore dimensionality reduction, dynamic modeling in latent space, and the impact of dimensionality reduction on model accuracy.

This PhD research focuses on developing and validating numerical models to study the effects of water injection on the acoustic and thermal environment during rocket launch. The work will involve multi-phase flow modeling, acoustic and thermal simulations, and comparisons with experimental data from the MARTEL test bench.

PhD research focused on understanding and identifying defects in irradiated silicon detectors that cause Dark Current Random Telegraph Signal (DC-RTS), leading to image degradation in space applications.

This PhD research aims to characterize the radar cross section (RCS) of electric thruster plasma plumes. The work will involve numerical simulation using a multi-physics tool, development of advanced signal processing techniques for RCS measurement in reverberant environments, and experimental characterization in both anechoic and reverberant chambers.

This research project focuses on developing a multi-sensor fusion approach to estimate bathymetry and associated uncertainty. The project will integrate existing methods, develop new agile methods for various sensors, and incorporate uncertainty estimation for fusion. The goal is to create a new global atlas of bathymetric data.

This research position focuses on improving the accuracy and capabilities of DTM_nrt, an AI-based thermosphere density forecast model. The successful candidate will investigate model limitations, explore data assimilation techniques, and develop enhancements to the model's performance.

This project aims to improve river flood modeling by combining data from the SWOT and CO3D missions. Researchers will use CO3D's high-resolution topography to refine SWOT-derived bathymetry, particularly in narrow and complex river reaches. The project will also investigate the potential of CO3D for surface velocity retrieval and discharge estimation.

This PhD project investigates the impact of blue economy interventions (marine protected areas, mariculture, eco-tourism) on poverty and outmigration in coastal villages of Madagascar. Using satellite imagery, AI algorithms, and statistical methods, the research will assess the causal link between blue economy development and socioeconomic outcomes over a 20-year period.

This PhD research aims to develop a method for predicting the fatigue life of metal parts produced by L-PBF additive manufacturing, considering the influence of defects. The research will involve developing a two-scale approach linking a local model detailing defects to a large-scale model of the assembled structure.

This PhD research aims to improve the reliability of antenna measurements by developing new methods for assessing far-field patterns from raw data and quantifying uncorrectable uncertainties. The research will explore narrow-band delay-based models, wavelet-based deconvolution, and stochastic methods to address challenges related to spurious scatterings and environmental randomness.

CNES is developing a sustainable water recycling system for space missions using photocatalytic degradation and in situ reactive oxygen nitrogen species (RONS) generation. The system integrates iron oxide nanoparticles and plasma-generated hydrogen peroxide to degrade organic and inorganic pollutants in wastewater.