Cryo-CMOS electronics: Thermal effects and electrical performance in FDSOI MOSFETs down to very low temperature
The post-doctoral subject focuses on studying thermal effects and electrical performance in FDSOI MOSFET transistors down to very low temperature for cryogenic applications, such as quantum computers and space applications. The goal is to model and characterize STMicroelectronics' 28FDSOI technology down to 4K and below, concentrating on self-heating and its impacts on circuit performance. The work includes DC and RF measurements, studying the back bias effect, exploring thermal couplings, and associated modeling. The project also aims to integrate these models into a 4K-valid Process Design Kit (PDK) to optimize circuits operating at very low temperatures. This work is part of the IRT Qloop project, in collaboration with STMicroelectronics. The results will contribute to advancing Cryo-CMOS electronics and the development of high-performance quantum computers.
Exploratory study of actinium-225 production capabilities in research reactors and particle accelerators
This postdoctoral research project will examine various methods of producing the medical radioisotope 225Ac. These methods will involve irradiating 226Ra using either a material testing reactor (such as the Jules Horowitz Reactor) or a particle accelerator (such as a cyclotron or a rhodotron). The study will determine the optimal conditions for producing 225Ac, including the type and energy of the incident particles, the target material used, and the corresponding production yields, as well as the quantity of contaminants generated.
The first part of the work will involve modelling the irradiation characteristics in research reactors and particle accelerators. This modelling will be carried out at the Department of Reactor Studies at the IRESNE Institute, at the CEA Cadarache site. Monte Carlo simulations using TRIPOLI4®, GEANT4 and PHITS – developed by the CEA, CERN and JAEA, respectively – will be employed to model the JHR and the particle accelerators.
The second part of the project will be carried out in close collaboration with several CEA laboratories. These laboratories will host the postdoctoral researcher on an ad hoc basis to support them through the subsequent stages of the project.
The CHICADE facility in Cadarache is responsible for designing the targets. The proposed work involves identifying the main steps for manufacturing the targets by electrodeposition, starting with a stock of 226Ra-containing material. If possible, a feasibility study will also be conducted on non-irradiated targets with the same properties (cerium/barium model material).
In collaboration with the DRMP units responsible for modelling the thermomechanical aspects of the targets, the proposed work will also involve conducting a feasibility study on the ion irradiation of a model target at a facility such as JANNuS-Saclay or GANIL.
Exploring the atomic configuration space with generative AI for the simulation of chemically disordered nuclear materials
How do you predict a material's properties when the number of possible atomic configurations exceeds 2^2500? That is the bottleneck our IRESNE (nuclear fuel physics) and LIST (AI) teams have just cracked with PULSE, a generative (VAE) method published in Nature Scientific Reports, already cutting computational cost by more than two orders of magnitude (22,282 CPU hours down to 85 on a test case). With no known equivalent in the international literature, PULSE positions CEA as a pioneer in generative sampling of the configuration space of chemically disordered materials.
This 24-month postdoc gives you the opportunity to drive this method toward its next generation, leading three ambitious, parallel research axes: pushing model accuracy on systems of several thousand atoms with an IWAE architecture; equipping it with the ability to quantify its own uncertainty — a prerequisite for any use in nuclear safety; and, in the second year, tackling a high-value exploratory axis — generalizing PULSE to a continuous latent space, opening the door to any disordered crystal or alloy.
You will work at the heart of an all-CEA consortium bringing together two complementary strengths — atomistic nuclear fuel physics at IRESNE and state-of-the-art generative AI at LIST — with access to CEA supercomputers, the freedom to publish in top-tier journals, and the prospect of seeing your results feed directly into reactor safety analyses through the PLEIADES platform. A position built for a curious mind who wants to combine cutting-edge generative AI research with concrete impact on a strategic nuclear-energy challenge.
Improvement of High-Temperature Electrolyzer Interconnect Performance
High-Temperature Electrolyzers (HTEs) are currently being developed at the CEA for the production of “green” hydrogen. One of the components, the stainless-steel interconnect, is affected by two phenomena that progressively reduce cell efficiency: surface oxidation and chromium oxide volatilization. For these reasons, protective coatings are being developed at the CEA and with industrial partners. The performance of these samples (oxidation behavior, electrical resistance, etc.) must be evaluated both in contact with air, in contact with an H2/H2O mixture, and under dual-atmosphere conditions with the two environments on either side of the sample.
The proposed postdoctoral position includes several missions presented below:
• Development of an experimental setup to evaluate the oxidation behavior and area-specific resistance of coated and uncoated samples under all environmental conditions.
• Investigation of the observed phenomena using the many characterization techniques available at the CEA (SEM, Raman microscopy, TEM, GD-OES, XPS, XRD, etc.).
• Proposal of the degradation mechanisms involved and identification of the most relevant coating for industrial applications.
Advanced fuzzing for software supply-chain security
IoT devices (routers, video surveillance systems, etc.) rely on binary code to operate. This code often incorporates thousands of pre-existing software components, mostly drawn from open-source libraries whose code is freely accessible online. This complexity opens the door to software supply chain attacks, notably through the insertion of backdoors or the exploitation of known vulnerabilities.
The SECUBIC project aims to enhance the detection of these vulnerabilities within IoT firmware. In this context, the candidate will contribute to deepening existing research work and will take part in the development of new fuzzing and static analysis techniques designed to prevent and detect such attacks.
Cell manufacturing and electrochemical testing of solid-state batteries
Holding a PhD in electrochemistry, materials science, chemistry, or process engineering, the postdoctoral researcher will work closely with project partners on the development of manufacturing processes and prototyping of solid-state battery cells of 4?? generation (Li/NMC high-nickel) and 5?? generation (Li/Sulfur).
The work will focus on electrode shaping and assembly of solid-state cells, using processes such as coating, extrusion, and alternative approaches including 3D printing. These processes will be optimized to produce prototype cells (button cells and pouch format) with capacities up to 1 Ah, incorporating optimized interfaces. The cells will then be electrochemically tested to evaluate performance in terms of specific capacity, coulombic efficiency, and cycling stability.
Most experimental work will be conducted in controlled environments (gloveboxes), with regular characterization of both electrodes and assembled cells. Main responsibilities will include:
- Contributing to the definition of test plans based on internal data and literature,
- Developing and optimizing manufacturing processes for electrodes and solid-state cells,
- Producing and testing Gen4b and Gen5 prototype cells,
- Evaluating electrochemical performance and analyzing results,
- Presenting results clearly and concisely,
- Proposing improvements, ensuring smooth laboratory operations, and adhering to safety and quality standards,
- Disseminating research through publications, scientific presentations,
Thermal properties of 3D aluminum nitride structures for electronic packaging
The 12-month postdoctoral fellowship is part of the overall 3DNAMIC project, funded by the Occitanie region and involving the Materials platform of the DRTDOCC department and the Laplace laboratory. A thesis began in December 2024 aimed at “the study and characterization of 3D aluminum nitride ceramics for the thermal packaging and management of electronic components.”
The postdoc is scheduled to begin at approximately in September 2026, with the following main objectives:
Objective 1: Perform a comparative analysis of the thermal properties of ceramics produced by AF elements and on model structures using different materials available in the CEA materials platform.
Objective 3: Propose, qualify, and validate, numerically and then experimentally, heat dissipation structures for ceramics obtained by FA as part of the 3DNAMIC project.
In-situ 4D tracking of microstructural evolution in atomistic simulations
The exponential growth of high-performance computing has enabled atomistic simulations involving billions or even trillions of particles, offering unprecedented insight into complex physical phenomena. However, these simulations generate massive amounts of data, making storage and post-processing increasingly restrictive. To overcome this limitation, on-the-fly (in-situ) analysis has emerged as a key approach for reducing stored data by extracting and compressing relevant information during runtime without significantly affecting simulation performance.
In this context, tracking the four-dimensional (space and time) microstructural evolution of materials under extreme conditions is a major scientific challenge. Atomistic simulations provide a unique spatial resolution to analyze crystalline defects such as dislocations, twinning, vacancies and pores, which govern dynamic phase transformations, melting, damage and mechanical behavior. By capturing their spatio-temporal evolution, it becomes possible to study their statistics, correlations and collective effects in out-of-equilibrium regimes, leading to more accurate predictive material models.
This project builds on advances of the exaNBody high-performance computing platform and a recently developed in-situ clustering method in the ExaStamp molecular dynamics code at CEA. This method projects atomic information onto a 3D Eulerian grid to perform real-time clustering. The objective is to extend this approach to full 4D tracking, enabling the time-resolved monitoring of clusters. This will allow dynamic graph-based analysis of their evolution, including changes in size, shape and temporal behavior, providing new insights into microstructural dynamics at the atomic scale.
Development of an innovative instrumentation architecture using an array of magneto-resistive sensors to create a fast tomography system for fuel cells
Developing an innovative instrumentation architecture using an array of magneto-resistive sensors to create a rapid tomography system for fuel cells.
The goal is to develop a TRL 4 demonstrator in the laboratory to demonstrate a proof of
concept on a low-temperature fuel cell stack. This will include four measurement boards
with several dozen of synchronized magnetic sensors for simultaneous acquisitions. Experimental results and a description of the instrumentation system will be published. Historical data will be used to validate current density resolution algorithms and compare their performance to solutions based on Physics Informed Neural Network. Estimated current density results will be used for an additional publication.
The instrumentation system will be integrated into a CEA test bench dedicated to optimal control, transient observation, fault detection and exploration of defect propagation phenomena. This approach will offer dynamic and non-invasive observation of current distribution in the fuel cell, thereby improving the understanding of its operation and facilitating the optimization of its performance and lifespan.
Study of the Velocity-Vorticity-Pression formulation for discretising the Navier-Stokes equations.
The incompressible Navier-Stokes equations are among the most widely used models to describe the flow of a Newtonian fluid (i.e. a fluid whose viscosity is independent of the external forces applied to the fluid). These equations model the fluid's velocity field and pressure field. The first of the two equations is none other than Newton's law, while the second derives from the conservation of mass in the case of an incompressible fluid (the divergence of velocity vanishes). The numerical approximation of these equations is a real challenge because of their three-dimensional and unsteady nature, the vanishing divergence constraint and the non-linearity of the convection term. Various discretisation methods exist, but for most of them, the mass conservation equation is not satisfied exactly. An alternative is to introduce the vorticity of the fluid as an additional unknown, equal to the curl of the velocity. The Navier-Stokes equations are then rewritten with three equations. The post-doc involves studying this formulation from a theoretical and numerical point of view and proposing an efficient algorithm for solving it, in the TrioCFD code.