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.
X-ray metrology and spectrometry for medical imaging
This 12-month postdoctoral position focuses on X-ray metrology and spectrometry for medical imaging. The context is the need for beam-quality traceability, since current standards (IEC 61267) do not cover the new filtration combinations (silver, gold, tin) used in spectral computed tomography (sCT), a technique involved in over 60 million CT exams annually in Europe. The position comprises two independent strands. The first (tasks 1-3) covers drafting methodological guides, qualifying LNHB's two spectrometry benches (CdTe and HPGe), establishing new reference radiation conditions, on-site clinical measurements, and participation in an inter-laboratory comparison. The second strand (tasks 4-5) concerns an instrumented dosimeter dedicated to radiological imaging, stemming from a thesis currently being finalized: pre-series fabrication, calibration, full metrological characterization, clinical validation in a hospital setting, and building a demonstrator.
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.
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.
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.
Integrating dynamic CRDTs replicas
Existing modeling frameworks have limited collaboration capabilities. Collaboration at the model level is one of the top desired features. However, most solutions rely on cloud-based and centralized databases as their technological solution. While these solutions ease collaboration among connected partners by employing concurrency control techniques, they do not support disconnected collaboration scenarios, which is an important feature for designing local-first software. This situation presents a significant compromise: utilizing cloud-based solutions with loss of data ownership control versus adopting separate instances without collaborative capabilities.
The objective of this postdoctoral project is to contribute to and extend an existing local-first Model-Based Systems Engineering (MBSE) framework, built upon specialized Conflict-free Replicated Data Types (CRDTs). The goal is to enable real-time collaboration through modeling-specific CRDTs. The proposed approach involves extending a middleware communication layer utilizing CRDTs to
seamlessly synchronize distributed, offline-capable engineering models.
The postdoctoral researcher will conduct a state-of-the-art review of communication and group membership approaches in P2P environments. One major issue to be taken into account is the entry and exit of members in a group, so the CRDT state is always
coherent. The components will be integrated into our CRDT and modeling framework.
Design and development of a modular high-side test bench for application validation of Grand Gap components
Wide bandgap transistors (GaN, SiC) play a key role in power electronics, but their industrial integration remains hampered by implementation difficulties. The high-side component, within a bridge arm structure, is particularly sensitive to voltage and current transients, which are highly dependent on routing, topology, and switching modes (ZVS, ZCS). Its floating nature makes measurements complex and can disrupt switching during application testing. A methodology adapted to fast transients was developed during a thesis, resulting in a patented test bench for characterizing low-side components. The subject of the postdoctoral research presented here aims to adapt this methodology to high-side components, which are more complex to drive and measure, in order to characterize and model aging due to gate transients under realistic conditions. The test bench will enable the generation of reproducible stress profiles on low-side and high-side components, and the precise measurement of key parameters such as threshold voltage and dynamic instabilities. To achieve these objectives, a new bench will be designed, incorporating specific control and measurement systems, with a view to application testing and targeted aging tests.
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Diamond-based electrochemical sensors for monitoring water pollution in urban environments
This postdoctoral position is offered by CEA List as part of the European UrbaQuantum project ("A novel, Integrated Approach to Urban Water Quality Monitoring, Management and Valorisation"), part of the HORIZON-CL6-2024-ZEROPOLLUTION-02 call for projects. The main objective of this project is to develop, in response to climate change, sensors, models, and protocols for better management of the water cycle in urban environments.
At the Sensors and Instrumentation for Measurement Laboratory (LCIM)of CEA List the postdoctoral fellow will contribute to the development of electrochemical sensors based on synthetic diamond and associated measurement protocols for the detection of pollutants such as pharmaceuticals, heavy metals, PFAS, and pesticides. These sensors will be miniaturized and integrated into a microfluidic cell, in partnership with CEA-Leti, then tested under real-world field conditions.
High-performance computing using CMOS technology at cryogenic temperature
Advances in materials, transistor architectures, and lithography technologies have enabled exponential growth in the performance and energy efficiency of integrated circuits. New research directions, including operation at cryogenic temperatures, could lead to further progress. Cryogenic electronics, essential for manipulating qubits at very low temperatures, is rapidly developing. Processors operating at 4.2 K using 1.4 zJ per operation have been proposed, based on superconducting electronics. Another approach involves creating very fast sequential processors using specific technologies and low temperatures, reducing energy dissipation but requiring cooling. At low temperatures, the performance of advanced CMOS transistors increases, allowing operation at lower voltages and higher operating frequencies. This could improve the sequential efficiency of computers and simplify the parallelization of software code. However, materials and component architectures need to be rethought to maximize the benefits of low temperatures. The post-doctoral project aims to determine whether cryogenic temperatures offer sufficient performance gains for CMOS or should be viewed as a catalyst for new high-performance computing technologies. The goal is particularly to assess the increase in processing speed with conventional silicon components at low temperatures, integrating measurements and simulations.
Digital correction of the health status of an electrical network
Cable faults are generally detected when communication is interrupted, resulting in significant repair costs and downtime. Additionally, data integrity becomes a major concern due to the increased threats of attacks and intrusions on electrical networks, which can disrupt communication. Being able to distinguish between disruptions caused by the degradation of the physical layer of an electrical network and an ongoing attack on the energy network will help guide decision-making regarding corrective operations, particularly network reconfiguration and predictive maintenance, to ensure network resilience. This study proposes to investigate the relationship between incipient faults in cables and their impact on data integrity in the context of Power Line Communication (PLC). The work will be based on deploying instrumentation using electrical reflectometry, combining distributed sensors and AI algorithms for online diagnosis of incipient faults in electrical networks. In the presence of certain faults, advanced AI methods will be applied to correct the state of the health of the electrical network's physical layer, thereby ensuring its reliability.