761 English-speaking jobs in Occitania

This PhD research aims to develop a numerical model predicting the transition from multipactor to RF discharge inception in high-frequency and radio-frequency payloads. The work will investigate electron avalanche processes, gas ionization dynamics, and the influence of geometry and material properties.

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.

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.

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 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 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.

This thesis investigates the impact of UV radiation on contaminant morphology through photofixation. The research aims to identify the chemical species involved in UV-contaminant interactions and establish a protocol to characterize these reactions.

This thesis develops AI tools to optimize plant cultivation in closed-loop life support systems for space missions. It focuses on using machine learning and computer vision to estimate plant and environmental states, and reinforcement learning to compute autonomous cultivation strategies.

This doctoral project focuses on designing robust attitude control laws for balloon-borne pointing systems. The work will involve developing control techniques that address system uncertainties and actuator limitations, including online adaptation strategies and control allocation schemes. Validation will include robustness analysis and experimental testing on a CNES test-bench.

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 focuses on understanding transient X-ray events from compact objects like black holes and neutron stars. The student will analyze data from the XMM-Newton observatory and other telescopes to study phenomena such as X-ray binaries, cataclysmic variables, and tidal disruption events. The goal is to improve our understanding of accretion processes, the growth of supermassive black holes, and the evolution of compact objects.

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 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.

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 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 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 PhD project develops physics-constrained deep learning algorithms for BIOMASS P-band SAR tomography applications. The research integrates electromagnetic scattering principles into neural network architectures to achieve accurate forest structure reconstruction.

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 research investigates the neural and cognitive adaptations to hypobaric environments simulating future lunar habitats. Using neuroimaging and physiological monitoring, the study examines the effects of reduced ambient pressure on brain function, autonomic regulation, and cognitive performance during simulated lunar habitat tasks.