High mobility mobile manipulator control in a dynamic context
The development of mobile manipulators capable of adapting to new conditions is a major step forward in the development of new means of production, whether for industrial or agricultural applications. Such technologies enable repetitive tasks to be carried out with precision and without the constraints of limited workspace. Nevertheless, the efficiency of such robots depends on their adaptation to the variability of the evolutionary context and the task to be performed. This thesis therefore proposes to design mechanisms for adapting the sensory-motor behaviors of this type of robot, in order to ensure that their actions are appropriate to the situation. It envisages extending the reconfiguration capabilities of perception and control approaches through the contribution of Artificial Intelligence, here understood in the sense of deep learning. The aim is to develop new decision-making architectures capable of optimizing robotic behaviors for mobile handling in changing contexts (notably indoor-outdoor), and for carrying out a range of precision tasks.
Modelling/Simulation of the synthesis of anti-corrosion coatings using the MOCVD process for low-carbon energy production
The durability of materials used in many areas of energy production is limited by their degradation in the operating environment, which is often oxidising and at high temperature. This is particularly true of High Temperature Electrolysers (HTE) for the production of ‘green’ hydrogen, or the fuel cladding used in nuclear reactors to produce electricity. Anti-corrosion coatings can/should be applied to improve the lifespan of these installations, thereby conserving resources. A process for synthesising coatings using a reactive vapour route with liquid organometallic precursors (DLI - MOCVD) appears to be a very promising process.
The aim of this thesis is to model and simulate the DLI-MOCVD coating synthesis process for the two applications proposed above. Simulation results (deposition rate, deposit composition, spatial homogeneity) will be compared with experimental results from large-scale ‘pilot’ reactors at the CEA in order to optimise the model's input parameters. On the basis of this CFD simulation/experiments dialogue, the optimum conditions for deposition on a scale 1 component will be proposed. A coupling between CFD simulations and Machine Learning will be developed to accelerate the change of scale and the optimisation of scale 1 deposits.
Radiological large-scale accident dosimetry: use of EPR spectroscopy for population triage by measurements of smartphone screens
In the event of a large-scale radiological emergency involving sources of external irradiation, methods are needed to identify which members of the population have been exposed and require priority care. To date, there are no operational methods for such sorting. Smartphone touch screen lenses retain traces of ionizing radiation through the formation of so-called “radiation-induced” defects.Measuring and quantifying these punctual defects, in particular by electron paramagnetic resonance (EPR) spectroscopy, makes itpossible to estimate the dose deposited in the glass, and thus the exposure associated with irradiation. The thesis work proposed herefocuses in particular on the alkali-aluminosilicate glasses used in cell phone touch screens, which are currently the best candidates fordeveloping new measurement capabilities in the context of accidents involving large numbers of victims.
We will focus in particular on identifying point defects as a function of the glass model used in smartphones by simulating EPR spectra in order to optimize the proposed dosimetry method.
Integrated System for Adaptive Antenna Tuning and Synthesized Impedance in the Sub-6 GHz Band for Next-Generation RF Systems.
The growing adoption of sub-6 GHz RF systems for 5G, IoT, and wearable technologies has created a critical demand for compact, efficient, and adaptive solutions to enhance energy transfer, mitigate environmental detuning effects, and enable advanced sensing capabilities. This thesis proposes an innovative system-on-chip (SoC) that integrates an Antenna Tuning Unit (ATU) and a Synthesized Impedance Module (SIM) to address these challenges. By combining in-situ impedance measurement and dynamic re-adaptation, the system resolves a key limitation of miniature antennas—their extreme sensitivity to environmental perturbations, such as proximity to the human body or metal surfaces. Moreover, the integration of a Synthesized Impedance Module brings additional versatility by enabling the emulation of complex loads. This capability not only optimizes energy transfer but also allows for advanced functionality, such as material characterization and environmental sensing around the antenna.
A central focus of this research is the co-integration of a Vector Network Analyzer (VNA) with a broadband post-matching network (PMN) and a Synthesized Impedance Module. This combined architecture provides real-time impedance monitoring, dynamic tuning, and the generation of specific impedance profiles critical for characterizing the antenna's response under various scenarios. Guaranteed operation in the 100 MHz–6 GHz band is achieved while maintaining low power consumption through efficient duty cycling.
. Profile Sought : are you passionate about electronics and microelectronics and eager to contribute to a major technological breakthrough? We are looking for a motivated and curious candidate with the following qualifications:
. Education
Graduate of an engineering school or holder of a master’s degree in electronics or microelectronics.
Technical Skills
Strong knowledge of transistor technologies (CMOS, Bipolar, GaN…).
Expertise in analog/RF design.
Experience with design tools such as ADS and/or Cadence.
Programming
Basic skills in Python, MATLAB, or similar programming languages.
Additional Experience
Prior experience in integrated circuit design would be a valuable asset.
. Why Apply: you will have the opportunity to work on cutting-edge technologies in an innovative and collaborative research environment. You will be guided by renowned experts in the field to tackle exciting scientific and technical challenges.
Contacts: PhD. Ghita Yaakoubi Khbiza: ghita.yaakoubikhbiza@cea.fr, HDR. Serge Bories: serge.bories@cea.fr
Point Spread Function Modelling for Space Telescopes with a Differentiable Optical Model
Context
Weak gravitational lensing [1] is a powerful probe of the Large Scale Structure of our Universe. Cosmologists use weak lensing to study the nature of dark matter and its spatial distribution. Weak lensing missions require highly accurate shape measurements of galaxy images. The instrumental response of the telescope, called the point spread function (PSF), produces a deformation of the observed images. This deformation can be mistaken for the effects of weak lensing in the galaxy images, thus being one of the primary sources of systematic error when doing weak lensing science. Therefore, estimating a reliable and accurate PSF model is crucial for the success of any weak lensing mission [2]. The PSF field can be interpreted as a convolutional kernel that affects each of our observations of interest, which varies spatially, spectrally, and temporally. The PSF model needs to be able to cope with each of these variations. We use specific stars considered point sources in the field of view to constrain our PSF model. These stars, which are unresolved objects, provide us with degraded samples of the PSF field. The observations go through different degradations depending on the properties of the telescope. These degradations include undersampling, integration over the instrument passband, and additive noise. We finally build the PSF model using these degraded observations and then use the model to infer the PSF at the position of galaxies. This procedure constitutes the ill-posed inverse problem of PSF modelling. See [3] for a recent review on PSF modelling.
The recently launched Euclid survey represents one of the most complex challenges for PSF modelling. Because of the very broad passband of Euclid’s visible imager (VIS) ranging from 550nm to 900nm, PSF models need to capture not only the PSF field spatial variations but also its chromatic variations. Each star observation is integrated with the object’s spectral energy distribution (SED) over the whole VIS passband. As the observations are undersampled, a super-resolution step is also required. A recent model coined WaveDiff [4] was proposed to tackle the PSF modelling problem for Euclid and is based on a differentiable optical model. WaveDiff achieved state-of-the-art performance and is currently being tested with recent observations from the Euclid survey.
The James Webb Space Telescope (JWST) was recently launched and is producing outstanding observations. The COSMOS-Web collaboration [5] is a wide-field JWST treasury program that maps a contiguous 0.6 deg2 field. The COSMOS-Web observations are available and provide a unique opportunity to test and develop a precise PSF model for JWST. In this context, several science cases, on top of weak gravitational lensing studies, can vastly profit from a precise PSF model. For example, strong gravitational lensing [6], where the PSF plays a crucial role in reconstruction, and exoplanet imaging [7], where the PSF speckles can mimic the appearance of exoplanets, therefore subtracting an accurate and precise PSF model is essential to improve the imaging and detection of exoplanets.
PhD project
The candidate will aim to develop more accurate and performant PSF models for space-based telescopes exploiting a differentiable optical framework and focus the effort on Euclid and JWST.
The WaveDiff model is based on the wavefront space and does not consider pixel-based or detector-level effects. These pixel errors cannot be modelled accurately in the wavefront as they naturally arise directly on the detectors and are unrelated to the telescope’s optic aberrations. Therefore, as a first direction, we will extend the PSF modelling approach, considering the detector-level effect by combining a parametric and data-driven (learned) approach. We will exploit the automatic differentiation capabilities of machine learning frameworks (e.g. TensorFlow, Pytorch, JAX) of the WaveDiff PSF model to accomplish the objective.
As a second direction, we will consider the joint estimation of the PSF field and the stellar Spectral Energy Densities (SEDs) by exploiting repeated exposures or dithers. The goal is to improve and calibrate the original SED estimation by exploiting the PSF modelling information. We will rely on our PSF model, and repeated observations of the same object will change the star image (as it is imaged on different focal plane positions) but will share the same SEDs.
Another direction will be to extend WaveDiff for more general astronomical observatories like JWST with smaller fields of view. We will need to constrain the PSF model with observations from several bands to build a unique PSF model constrained by more information. The objective is to develop the next PSF model for JWST that is available for widespread use, which we will validate with the available real data from the COSMOS-Web JWST program.
The following direction will be to extend the performance of WaveDiff by including a continuous field in the form of an implicit neural representations [8], or neural fields (NeRF) [9], to address the spatial variations of the PSF in the wavefront space with a more powerful and flexible model.
Finally, throughout the PhD, the candidate will collaborate on Euclid’s data-driven PSF modelling effort, which consists of applying WaveDiff to real Euclid data, and the COSMOS-Web collaboration to exploit JWST observations.
References
[1] R. Mandelbaum. “Weak Lensing for Precision Cosmology”. In: Annual Review of Astronomy and Astro- physics 56 (2018), pp. 393–433. doi: 10.1146/annurev-astro-081817-051928. arXiv: 1710.03235.
[2] T. I. Liaudat et al. “Multi-CCD modelling of the point spread function”. In: A&A 646 (2021), A27. doi:10.1051/0004-6361/202039584.
[3] T. I. Liaudat, J.-L. Starck, and M. Kilbinger. “Point spread function modelling for astronomical telescopes: a review focused on weak gravitational lensing studies”. In: Frontiers in Astronomy and Space Sciences 10 (2023). doi: 10.3389/fspas.2023.1158213.
[4] T. I. Liaudat, J.-L. Starck, M. Kilbinger, and P.-A. Frugier. “Rethinking data-driven point spread function modeling with a differentiable optical model”. In: Inverse Problems 39.3 (Feb. 2023), p. 035008. doi:10.1088/1361-6420/acb664.
[5] C. M. Casey et al. “COSMOS-Web: An Overview of the JWST Cosmic Origins Survey”. In: The Astrophysical Journal 954.1 (Aug. 2023), p. 31. doi: 10.3847/1538-4357/acc2bc.
[6] A. Acebron et al. “The Next Step in Galaxy Cluster Strong Lensing: Modeling the Surface Brightness of Multiply Imaged Sources”. In: ApJ 976.1, 110 (Nov. 2024), p. 110. doi: 10.3847/1538-4357/ad8343. arXiv: 2410.01883 [astro-ph.GA].
[7] B. Y. Feng et al. “Exoplanet Imaging via Differentiable Rendering”. In: IEEE Transactions on Computational Imaging 11 (2025), pp. 36–51. doi: 10.1109/TCI.2025.3525971.
[8] Y. Xie et al. “Neural Fields in Visual Computing and Beyond”. In: arXiv e-prints, arXiv:2111.11426 (Nov.2021), arXiv:2111.11426. doi: 10.48550/arXiv.2111.11426. arXiv: 2111.11426 [cs.CV].
[9] B. Mildenhall et al. “NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis”. In: arXiv e-prints, arXiv:2003.08934 (Mar. 2020), arXiv:2003.08934. doi: 10.48550/arXiv.2003.08934. arXiv:2003.08934 [cs.CV].
AI-assisted generation of Instruction Set Simulators
The simulation tools for digital architectures rely on various types of models with different levels of abstraction to meet the requirements of hardware/software co-design and co-validation. Among these models, higher-level ones enable rapid functional validation of software on target architectures.
Developing these functional models often involves a manual process, which is both tedious and error-prone. When low-level RTL (Register Transfer Level) descriptions are available, they serve as a foundation for deriving higher-level models, such as functional ones. Preliminary work at CEA has resulted in an initial prototype based on MLIR (Multi-Level Intermediate Representation), demonstrating promising results in generating instruction execution functions from RTL descriptions.
The goal of this thesis is to further explore these initial efforts and subsequently automate the extraction of architectural states, leveraging the latest advancements in machine learning for EDA. The expected result is a comprehensive workflow for the automatic generation of functional simulators (a.k.a Instruction Set Simulators) from RTL, ensuring by construction the semantic consistency between the two abstraction levels.
Development of a multi-criteria comparison tool for electrochemical stationary storage systems
Use of stationary storage systems is now essential to keep pace with changes in the electricity grid and the growing integration of intermittent renewable energies such as solar and wind power. The choice of a storage solution is based on a number of criteria, including performance, lifetime, environmental impact, safety, regulatory constraints and, of course, economics.
The laboratory possesses comparative data on these different criteria, via experimental studies and feedback on existing systems. In addition, an initial software tool has been developed to assess environmental impact using LCA (Life Cycle Assessment). The aim of this thesis work is to integrate these different components into a broader comparison tool with a multi-criteria approach, targeting specific case studies and a limited number of storage technologies that have reached sufficient maturity for the available data to be reliable.
High yield strength austenitic stainless steels for nuclear applications: numerical design and experimental study
The PhD thesis is part of a project that aims at designing new austenitic stainless steels grades for nuclear applications, which are specifically suitable to in-service conditions encountered by the components and to the manufacturing process. More precisely, the subject deals with bolt steels achieved by controlled nitriding of powders which are then densified by hot isostatic pressing. Indeed, current bolt steel grades may suffer from stress corrosion cracking, while nitriding allows to increase the chromium content, which is beneficial from that point of view.
The study will start by the definition of specifications and associated criteria, then CALPHAD calculations in the Fe-Cr-Ni-Mo-X-N-C system will be done to define promising compositions. Then, selected compositions will be supplied as powders. The behaviour of powders during nitriding will be studied and modelled. Samples will be nitrided, densified and heat treated. One grade will be then selected and fully characterised: mechanical properties and deformation mechanisms, corrosion behaviour. One important objective is to demonstrate the advantages of the new grade compared to the industrial solution.
Space-time Modulated Electromagnetic Metasurfaces for Multi-functional Energy-Efficient Wireless Systems
Next-generation (XG) wireless systems envision an unprecedented network densification and the efficient use of the near-millimeter-wave (mmW) spectrum. Disruptive concepts are required to minimize the number of antenna systems and their power consumption. Reconfigurable intelligent surfaces (RISs) can provide high-gain beam-forming using simple devices (e.g. p-i-n diodes) to control their scattering properties of their unit-cells. However, the efficiency of an RIS and the wireless functions it can simultaneously realize, are bound by its inherent linearity and reciprocity.
Space-time modulated metasurfaces (STMMs) have recently emerged as a beam-forming solution overcoming fundamental limits of linear time-invariant systems. Leveraging an additional time-variation of the unit-cell response, with respect to RISs, an STMM can tailor at the same time angular and frequency spectra of the radiated fields, without using multiple active circuits as in current systems.
Most models for the design of STMMs are oversimplified and consider 1-D modulations in quasi-static temporal regime. The impact of spatial discretization and phase quantization is overlooked. The few reported prototypes are often electrically small, with a coarse (half-a-wavelength) period. Most demonstrators operate in reflection, below 17 GHz and enable only a 1-bit phase resolution. Independent far-field beam-steering at several frequencies has been proved in a single scan plane.
This Ph.D. thesis aims at modelling, designing and demonstrating electrically large and multi-functional transmissive STMM antennas with enhanced phase resolution and beam-forming capabilities. Efficient numerical models will enable the computation of the fields scattered by a STMM in far- and near-field regions, for arbitrary spatial and time modulation periods. Holographic and compressive sensing techniques will be proposed to jointly optimize the metasurface phase profile and the time-modulation waveforms, enabling harmonic beam-shaping. A thorough study of the effect of phase resolution, STMM period and time-modulation frequency on the performance, power consumption and complexity of the control electronics will be provided.
A transmissive STMM prototype based on p-i-n diodes and enabling a 2-bit phase resolution will be realized for the first time, building on the group background on space-modulated electronically reconfigurable flat lens antennas. It will work in a frequency range suited to terrestrial and satellite networks (17-31 GHz). Multiple antenna functionalities will be experimentally characterized using the same prototype, such as: (i) simultaneous and non-reciprocal 2-D beam-forming at different harmonics of the time-modulating signals, in either far-field or near-field region; (ii) pattern shaping at the fundamental frequency, using optimized time-sequences to increase the effective phase resolution.
The fundamental and experimental contributions of this research will broaden the physical insight on time-modulated metasurfaces and increase the maturity of this technology for energy-efficient smart antennas with applications to wireless networks and integrated communication and sensing systems. An intense dissemination activity in high-impact scientific journals of electrical engineering and applied physics is expected, given the novelty of the topic and the growing interest it triggers in several communities.