One-sided communication mechanisms for data decomposition in Monte Carlo particle transport applications
In the context of a Monte Carlo calculation for the evolution of a PWR (pressurized water reactor) core, it is necessary to compute a very large number of neutron-nucleus reaction rates, involving a data volume that can exceed the memory capacity of a compute node on current supercomputers. Within the Tripoli-5 framework, distributed memory architectures have been identified as targets for high-performance computing deployment. To leverage such architectures, data decomposition approaches must be used, particularly for reaction rates. However, with a classical parallelization method, processes have no particular affinity for the rates they host locally; on the contrary, each rate receives contributions uniformly from all processes. Access to decomposed data can be costly when it requires intensive use of communications. Nevertheless, one-sided communication mechanisms, such as MPI RMA (Message Passing Interface, Remote Memory Access), make these accesses easier both in terms of expression and performance.
The objective of this thesis is to propose a method for partial data decomposition relying on one-sided communication mechanisms to access remotely stored data, such as reaction rates. Such an approach will significantly reduce the volume of data stored in memory on each compute node without causing a significant degradation in performance.
Optimising the enzymatic degradation of polylactic acid (PLA) to produce biohydrogen (BioH2) through photofermentation.
This thesis project presents a novel method of producing biohydrogen (BioH2) through the enzymatic breakdown of polylactic acid (PLA), a bioplastic which is challenging to recycle. The aim is to optimise the hydrolysis of PLA into lactic acid, which can be metabolised directly by purple non-sulfur bacteria (PNSB) to produce BioH2 in anoxic conditions. The work will entail selecting high-performance esterases in collaboration with Génoscope CEA, expressing them in soluble form in model hosts such as E. coli, yeasts and PNSB, and optimising reaction conditions such as pH, temperature and concentration to maximise lactic acid production. The second phase will focus on enhancing photofermentation in a photobioreactor (PBR) with advanced control systems (LED, AI and CFD). Funded by the CEA and PUI Grenoble Alpes, this project is part of a circular economy approach, aiming to develop a scalable process for converting PLA waste into renewable energy in line with the challenges of the energy transition.
New generation of organic susbtrates for power conversion
Recent advances in electric motors and associated power electronics have led to a significant increase in power density requirements. This increase in power density means smaller heat exchange surfaces, which amplifies the challenges associated with dissipating the heat generated by power electronics components during operation. In fact, the lack of adequate heat dissipation causes electronic components to overheat, impacting their performance, durability, and reliability. Other issues related to cost, repairability, and thermomechanical constraints call into question traditional ceramic-based insulating thermal interfaces. It is therefore imperative to develop a new generation of heat-dissipating materials that take the system environment into account.
The objective of this thesis is to replace the ceramic substrate in power module systems, whose main role is to act as the system's dielectric layer, with a thermally conductive organic matrix composite. The current substrate has well-known limitations (fragility, poor interface, cycling limit, cost). The organic substrate must have the highest possible thermal conductivity (>3 W/m.k) in order to dissipate the heat emitted properly, while also being electrically insulating with a breakdown voltage of approximately 3kV/mm. It must also have a coefficient of thermal expansion (CTE) compatible with that of copper in order to eliminate delamination phenomena during the cycling undergone by the device during its lifetime. The innovation of the doctoral student's work will lie in the use of highly thermally conductive (nano)fillers that will be electrically insulated (insulating coating) and can be oriented in a polymer resin under external stimulus.
The development of the electrical insulating shell on the thermally conductive core will be carried out using the sol-gel method. The synthesis will be controlled and optimized in order to correlate the homogeneity and thickness of the coating with the dielectric and thermal performance of the (nano)composite. The charge/matrix interface (a potential source of phonon diffraction) will also be studied. A second part will focus on grafting magnetic nanoparticles (MNPs) onto thermally conductive (nano)fillers. Commercial MNPs will be evaluated (depending on requirements, grades synthesized in the laboratory may also be evaluated). The (nano)composites must have rheology compatible with pressing and/or injection processes.
Novel architecture and signal processing for mobile optical telecommunications
Free-Space Optical Communications (FSO) rely on transmitting data via light between two distant points, eliminating the need for fibers or cables. This approach is particularly valuable when wired connections are impractical or prohibitively expensive.
However, these links are highly susceptible to atmospheric conditions—fog, rain, dust, and thermal turbulence—which attenuate or distort the light beam, significantly degrading communication quality. Current solutions remain costly and limited, both in terms of optical compensation hardware and signal processing algorithms.
Within this framework, the thesis aims to design high-performance, robust mobile optical links capable of adapting to dynamic and disturbed environments. The study will focus on leveraging Silicon-based Optical Phased Arrays (OPAs)—a technology derived from low-cost LiDAR systems—offering a promising path toward compact, integrated, and cost-effective architectures.
The primary focus of the research will be developing advanced algorithmic approaches for signal processing and compensation. The PhD candidate will be tasked with designing a dedicated simulation environment to evaluate and validate architectural choices and algorithmic strategies before practical experimentation.
The overarching goal is to propose an integrated, flexible, and reliable architecture that ensures uninterrupted optical communication in motion, with potential applications in aerospace, space, and terrestrial domains.
Multipath-based Cooperative Simultaneous Localization & Mapping through Machine Learning
The goal of this PhD is to explore the potential of machine learning (ML) tools for simultaneous localization and mapping (SLAM) applications, while leveraging multipath radio signals between cooperative wireless devices.
The idea is to identify characteristic features of the propagation channels observed over multiple radio links, so as to jointly determine the relative positions of the mobile radio devices, as well as those of scattering objects present in their vicinity. Such radio features typically rely on the arrival times of multipath echos of the transmitted signals. The envisaged approach is expected to benefit from multipath correlation as the radio devices are moving, as well as from spatial diversity and information redundancy through multi-device cooperation. The developed solution will be evaluated on both real measurements collected with integrated Ultra Wideband devices in a reference indoor environment, and synthetic data generated with a Ray-Tracing simulator.
Possible applications of this research concern group navigation in complex and/or unknown environments (incl. fleets of drones or robots, firefighters…).
Integrated optical functions on microbolometer focal planes for uncooled infrared imaging
Thermal infrared imaging (wavelengths 8-14 µm) is a growing field, particularly in industry, transportation, and environment. It relies on a detection technology, microbolometers, for which CEA-Leti is at the forefront of the global state of the art. Integrating advanced optical functions directly onto the detectors is a very promising approach for improving performance, compactness, and cost in future infrared cameras.
The optical functions under consideration include spectral filtering, polarimetry, wavefront correction, and more. Some aim to enrich the image with information essential for applications such as absolute thermography (temperature and emissivity measurement), identification for automated scene interpretation (machine vision), gas detection, and others.
The proposed work will include the design, fabrication, and electro-optical characterization of functionalized microbolometer arrays. Using 3D electromagnetic simulation tools, the design of these optical functions will take into account the compatibility with our microbolometer technologies and the capabilities of our microfabrication facilities. Fabrication will take place in the CEA-Leti cleanrooms by dedicated personnel, but the candidate will participate in defining and monitoring the work. Finally, optical and electro-optical characterizations will be performed in our laboratory, if necessary with the development of dedicated characterization benches.
Hydrodynamic simulations of porous materials for ductile damage
The mechanical behavior of metallic materials under highly dynamical loading (schock) and especially their damage behavior is a topic of interest for the CEA-DAM. For tantalum, damage is ductile : by nucleation, growth and coalescence of voids within the material. Usual ductile damage models have been developed using the simplifying assumption that voids are isolated in the materials. However, recent studies by direct simulations explicitly describing a void population in the material (and experimental observations after failure) have shown the importance of void interaction for predicting ductile damage. Yet, the microscopical mechanisms of this interaction remain little known.
The objective of the PhD is to study the growth and coalescence phases of ductile damage through direct numerical simulations of a porous material undergoing dynamic loading. Hydrodynamic simulations, in which voids are explicitly meshed within a continuous matrix, will be used to study relevant scales of length and time. Monitoring the void population throughout the simulation will provide valuable information on the influence of void interaction during ductile damage. Firstly, the bulk behavior will be compared to the one predicted by usual models of isolated voids, showing the macroscopic effect of void interaction. Secondly, the evolution of the size distribution in the void population will be monitored. The last objective will be to understand microscopic void-to-void interaction. In order to take advantage of the wealth of simulation results, approaches based on artificial intelligence (neural networks on the graph associated with the pore population) will be used to learn the link between a void's neighborhood and its growth.
The doctoral student will have the opportunity to develop their skills in shock physics and mechanics, numerical simulations (with access to CEA-DAM supercomputers), and data science.
Modelling of Thermo-Fluid Phenomena in the Plasma Nozzle of the ELIPSE Process
The ELIPSE process (Elimination of Liquids by Plasma Under Water) is an innovative technology dedicated to the mineralization of organic effluents. It is based on the generation of a thermal plasma fully immersed in a water-filled reactor vessel, enabling extremely high temperatures and reactive conditions that promote the complete decomposition of organic compounds.
The proposed PhD research aims to develop a multiphysics numerical model describing the behavior of the process, particularly within the plasma nozzle, a key zone where the high-temperature gas jet from the torch interacts with the injected liquids.
The approach will rely on coupled thermo-aerodynamic modeling, integrating fluid dynamics, heat transfer, phase change phenomena, and turbulence effects. Using Computational Fluid Dynamics (CFD) tools, the study will characterize plasma–liquid interaction mechanisms and optimize the geometry and operating conditions of the process. This modeling will be compared and validated against complementary experimental data obtained from the ELIPSE setup, providing the necessary input for model calibration and validation.
This work will build upon previous research that has led to the development of thermal and hydraulic models of both the plasma torch and the reactor vessel. Integrating the new model within this framework will yield a comprehensive and coherent representation of the ELIPSE process. Such an approach represents a decisive step toward process optimization and industrial scale-up.
The ideal candidate will be a Master’s or final-year engineering student with a background in process engineering and/or numerical simulation, demonstrating a strong interest in physical modeling and computational approaches.
During this PhD, the candidate will develop and strengthen skills in multiphysics numerical modeling, advanced CFD simulation, and thermo-aerodynamic analysis of complex processes. They will also acquire solid experience in waste treatment, a rapidly expanding field with significant industrial and environmental relevance. These skills will provide strong career opportunities in applied research, process engineering, energy, and environmental sectors.
AI Enhanced MBSE framework for joint safety and security analysis of critical systems
Critical systems must simultaneously meet the requirements of both Safety (preventing unintentional failures that could lead to damage) and Security (protecting against malicious attacks). Traditionally, these two areas are treated separately, whereas they are interdependent: An attack (Security) can trigger a failure (Safety), and a functional flaw can be exploited as an attack vector.
MBSE approaches enable rigorous system modeling, but they don't always capture the explicit links between Safety [1] and Security [2]; risk analyses are manual, time-consuming and error-prone. The complexity of modern systems makes it necessary to automate the evaluation of Safety-Security trade-offs.
Joint safety/security MBSE modeling has been widely addressed in several research works such as [3], [4] and [5]. The scientific challenge of this thesis is to use AI to automate and improve the quality of analyses. What type of AI should we use for each analysis step? How can we detect conflicts between safety and security requirements? What are the criteria for assessing the contribution of AI to joint safety/security analysis?
Influence of battery system disassemblability on their environmental impacts
With the rise of electric mobility and Energy storage, the demand for batteries is rapidely increasing. But this growth raises a crucial question: how can we design batteries that are both high-performing, durable, and more environmentaly friendly ?
Without focusing on cell Chemistry, one promising approach lies in disassembly-oriented designs: making battery packs easier to disassemble could facilitate their repair, reuse, or recycling. However, a more easily dismantled design may also increase its mass or reduce the system's reliability, potentially affecting its overall lifetime.
This PhD aims to tackle this challenge by developing an analytical method to link the design of dismountable battery systems with their actual environmental impacts, while explicitly accounting for reliability aspects.
The PhD candidate will assess the ease of disassembly of different battery systems, quantify the environmental gains and losses compared to conventional designs, and help develop a decision-support tool to guide design choices. The proposed research will involve, among other tasks, Life Cycle Assessment (LCA) modelling coupled with battery performance and ageing models, as well as failure probabilities analysis.
This project takes place in a technological context driven by the growing need for resource circularity, the automation of disassembly processes, and the implementation of new European regulations on batteries. If offers a unique opportunity to contribute to the design of the next generation of sustainable battery systems.