778 English-speaking jobs in Occitania

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 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 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.

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 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 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.

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 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 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 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 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 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 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 thesis investigates the use of remote sensing data to improve hydrological modeling. The research will focus on optimizing a semi-distributed GR model using various remote sensing products, including snow cover, soil moisture, evapotranspiration, and water levels. The goal is to enhance model parameterization, improve consistency between simulated variables and observations, and increase the model's spatial and temporal transferability.

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 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 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.

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 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.