515 English-speaking jobs in Toulouse

This PhD thesis focuses on developing advanced image processing methods for space coronagraphs, specifically addressing systematics limiting JWST and Roman observations. The student will explore analytical approaches using JWST wavefront measurements and existing coronagraphic images, and develop hybrid methods combining optical modeling with telemetry and archive data. The goal is to improve exoplanet detection limits by removing starlight contamination and instrumental artifacts.

This research position focuses on bridging the gap between two Earth observation models: TAMRF and RELEO. The work will extend the TAMRF architecture to a fully attention-based system using Perceiver-IO, supporting additional sensors and incorporating exogenous variables. The researcher will also contribute to RELEO's training strategy and architecture validation.

This research project analyzes lightning activity observed by the MTG-LI instrument, focusing on flash and storm scales. The study will compare lightning properties and cloud characteristics over Europe, Africa, and the Atlantic Ocean.

This PhD research focuses on developing a new type of powder damper for mitigating micro-vibrations in satellites. The project will involve developing a dynamic model, characterizing the damper through vibration tests, and optimizing its design for maximum energy dissipation.

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 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 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.

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 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 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 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 thesis develops a hybrid navigation pipeline combining visual/inertial SLAM, physics- and geometry-grounded Vision Foundation Models, and 3D reconstruction techniques. The project aims to create robust navigation methods for complex environments, validated in simulations and on real robotic platforms.

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 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 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.

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 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.

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.