Power converters are essential in numerous applications such as industry, photovoltaic systems, electric vehicles, and data centers. Their conventional maintenance is often based on fixed schedules, leading to premature replacement of components and significant electronic waste. This PhD project aims to develop a novel non-invasive and low-cost ultrasound-based monitoring approach to assess the state of...

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The inspection of wafer surfaces is critical in microelectronics to detect defects affecting chip quality. Traditional methods, based on physical models, are limited in accuracy and computational efficiency. This thesis proposes using artificial intelligence (AI) to characterize and model wafer topography, leveraging optical interferometry techniques and advanced AI models. The goal is to develop AI...

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To increase the performance of quantum computers, three-dimensional (3D) integration is now the key! Using technologies such as flip-chip bonding, multi-layer wiring or even through-silicon vias (TSV), 3D integration offers solutions to increase the number of qubits on a processor, reduce signal loss and cross-talk and even improve thermal management. All of these aspects are...

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This PhD proposal will develop a container orchestration scheme for real-time applications, deployed on a continuum of heterogeneous computing resources in the embedded-edge-cloud space, with a specific focus on applications that require real-time guarantees. Applications, from autonomous vehicles, environment monitoring, or industrial automation, applications traditionally require high predictability with real-time guarantees, but they increasingly ask...

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Video Anomaly Detection (VAD) aims to automatically identify unusual events in video that deviate from normal patterns. Existing methods often rely on One-Class or Weakly Supervised learning: the former uses only normal data for training, while the latter leverages video-level labels. Recent advances in Vision-Language Models (VLMs) and Large Language Models (LLMs) have improved both...

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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...

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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...

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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...

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In the race towards building a quantum computer, there is a deep interest in fabricating devices based on the robust and scalable silicon FD-SOI technology. One example is the Josephson Field Effect Transistor (JoFET) whose operability relies on the high transparency of the interface between the superconducting source/drain regions and the semiconducting channel. Such transparency...

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This work aims to develop Advanced ultrathin cunductive layers (lt;10nm) by ALD (Atomic Layer Deposition)for électrodes use(resistivity lt;mOhm)of high density ionic capacitors fabricated on 3D complex structures (high aspect ratio 1:100). The preliminary effort will be focused on the deep analysis and the impact of interface formation between ionic layers and subseqquent electrode layers. One...

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This thesis falls within the field of cooled infrared detectors. The CEA-LETI-MINATEC Infrared Laboratory specializes in the design and manufacture of infrared camera prototypes used in defense, astronomy, environmental monitoring, and satellite meteorology. In this context of high-performance imaging, it is crucial to ensure optimal detector quality. However, manufacturing processes can introduce defects that can...

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The growing demand for III-V semiconductors in high-efficiency photovoltaics, quantum photonics, and advanced imaging technologies requires innovative and cost-effective fabrication methods. This PhD project focuses on developing plasma etching processes for In-based III-V semiconductors to produce high aspect ratio (HAR) structures on large wafers from 100 to 300 mm. The research addresses two key challenges:...

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Ultra-high-dose-rate FLASH radiotherapy is one of the most promising innovations of the last decade in radiation oncology. It has the potential to eradicate radioresistant tumours and reduce unwanted side effects, that in turn increases cure rates and improves patient quality of life. However, dosimetry infrastructure is lagging behind this clinical and technological advance, with current...

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Advanced nanoelectronics and quantum devices rely on ultrathin oxides and engineered interfaces whose chemical composition, stoichiometry and thickness must be controlled with sub-nanometer precision. LETI is installing the first 300-mm multi-energy XPS–HAXPES tool with angle-resolved capability, enabling quasi in situ chemical metrology from deposition to characterization. This PhD will develop quantitative, multi-energy and angle-resolved XPS/HAXPES...

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Through the Carnot SpectroRF exploratory project, CEA Leti is involved in radio-frequency sensor systems based on atomic optical spectroscopy. The idea behind the development is that these systems offer exceptional detection performance. These include high sensitivity´ (~nV.cm-1.Hz-0.5), very wide bandwidths (MHz- THz), wavelength-independent size (~cm) and no coupling with the environment. These advantages surpass the...

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The aim of this PhD thesis is to develop new clinical assessment methods using surface haptics technologies, developed at CEA List, and machine learning algorithms for testing and monitoring tactile-motor integration. In particular, the thesis will investigate and validate the development of a multimodal analytics pipeline that converts surface haptics signals and dexterity exercises inputs...

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Switches based on phase change materials (PCM) demonstrate excellent RF performance (FOM lt;10fs) and can be co-integrated into the BEOL of CMOS processes. However, their reliability is still very little studied today. Failure modes such as heater breakage, segregation, or the appearance of cavities in the material are shown during endurance tests, but the mechanisms...

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Block copolymers (BCP) are an industrial technology in full expansion, offering promising perspectives for material nanostructuring. These polymers, composed of chemically distinct block chains, self-assemble to form ordered structures at the nanometric scale. However, their current use is limited to specific nanostructuring per product (1 product = 1 nanostructuring), thus restricting their application potential. This...

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This PhD thesis offers a unique opportunity to work at the crossroads of electromagnetics, numerical simulations, and artificial intelligence, contributing to the development of next-generation intelligent sensing and recognition systems. The intern will join the Antenna amp; Propagation Laboratory at CEA-LETI, Grenoble (France), a world-class research environment equipped with state-of-the-art tools for propagation channel characterization...

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The proposed PhD work lies within the exploration of new supercapacitor and hybrid energy storage technologies, aiming to combine miniaturization, high power density, and CMOS process compatibility. The hosting laboratory (LTEI/DCOS/LCRE) has recognized expertise in thin-film integration and dielectric material engineering, offering unique opportunities to investigate ferroelectric (FE) and antiferroelectric (AFE) behaviors in doped hafnium...

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Complementary Field Effect Transistors (CFETs) represent a new generation of vertically stacked CMOS devices, offering a promising path to continue transistor miniaturization and to meet the requirements of high-performance computing. The objective of this PhD work is to study and optimize the strain engineering of the transistor channel in order to enhance carrier mobility and...

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Embedded systems are increasingly used in critical infrastructures (e.g., energy production networks) and are therefore prime targets for malicious actors. The use of intrusion detection systems (IDS) that dynamically analyze the systemapos;s state is becoming necessary to detect an attack before its impacts become harmful. The IDS that interest us are based on machine learning...

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The integration of renewable energy sources (RES) has become an important issue for power converters. The increasing number of these converters and their average utilization rate allows for a rethink of energy exchange management at the system level. This leads us to the concept of an energy hub, which can interface, for example, a photovoltaic...

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The laboratory, reknown for its expertise in high-resolution and high-precision magnetic measurements, has been developing and providing for several decades successive generations of optically pumped helium-4 magnetometers. These instruments serve as reference sensors aboard the ESA Swarm mission satellites launched in late 2013, and will also equip the forthcoming NanoMagSat mission, scheduled to launch from...

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The application of gamma spectrometry to radiological characterization in nuclear facility decommissioning, requires the development of specific algorithms for automatic gamma spectrum analysis. In particular, the classification of concrete waste according to its level of contamination, is a crucial issue for controlling decommissioning costs. Within CEA/List, LNHB, in collaboration with CEA/DEDIP, has been involved for...

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Dispersion engineering (DE) refers to the control of how electromagnetic waves propagate in a structure by shaping the relationship between frequency and phase velocity. Using artificially engineered materials and surfaces, this relationship can be tailored to achieve non-conventional propagation behaviors, enabling precise control of dispersive effects in the system. In antenna design, dispersion engineering can...

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This PhD aims to design analog liquid neural networks for generative edge intelligence. Current neuromorphic architectures, although more efficient through in-memory computing, remain limited by their extreme parameter density and interconnection complexity, making their hardware implementation costly and difficult to scale. The Liquid Neural Networks (LNN), introduced by MIT at the algorithmic level, represent a...

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Quantum information technologies offers several promises in domains such as computation or secured communications. Because of their robustness against decoherence, photonic qubits are particularly interesting for quantum communications applications, even at room temperature. They also offers an alternative to other qubits technologies for quantum computing. For the large-scale deployment of those applications, it is necessary...

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Wireless power transfer (WPT) technologies are rapidly expanding, particularly for wireless charging of everyday electronic devices and for powering wireless communicating sensor nodes. However, their transmission ranges remain limited, and the high operating frequencies typically used prevent energy transfer in the presence of, or through, conductive media (such as metallic barriers or seawater). This constraint...

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The security of numerical systems relies on cryptographic chains of trust starting from the hardware up to end-user applications. The root of chain of trust is called a “root of trust” and takes the form a dedicated Integrated Circuit (IC), which stores and manipulates secrets. Thanks to countermeasures, those secrets are kept safe from extraction...

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The manufacturing of electronic equipment, and more specifically Printed Circuit Boards (PCBs), represents a significant share of the environmental impact of digital technologies, which must be minimized. Within a circular economy approach, the development of monitoring and diagnostic tools for assessing the health status of these boards could feed into the product’s digital passport and...

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This PhD topic offers a unique opportunity to enhance your skills in GaN power devices and develop cutting-edge architectures. You’ll work alongside a multidisciplinary team specializing in material engineering, characterization, device simulation, and electrical measurements. If you’re eager to innovate, expand your knowledge, and tackle state-of-the-art challenges, this position is a valuable asset to your...

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Illicit uses of images have dramatically risen with deepfake content manipulation or unauthorized access. Securing images at their source i.e., at the image sensor level, is key to addressing the challenges of this field of cybersecurity. The quot;trusted imagersquot; concept addresses the need to ensure image security, authentication, and encryption starting at the point of...

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This PhD research focuses on the integrated co-optimization of materials, fabrication processes and device architectures to enable high-performance RF transistors on advanced nanometer-scale technologies. The work aims to understand and improve key RF figures of merit—such as transit frequency, maximum oscillation frequency, noise behaviour and linearity—by establishing clear links between material choices, process innovations and...

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For next-generation microelectronics, Area Selective Deposition (ASD)is a promising approach to simplify integration schemes for the most advanced technology nodes. These ASD approaches need to be adapted according to a trio comprising the material to be deposited, the growth surface, and the inhibited surface. This PhD focuses on the area selective deposition of oxides (such...

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The blood-brain barrier (BBB) protects the brain by controlling exchanges between the blood and nervous tissue. However, current models struggle to accurately reproduce its complexity. This thesis aims at developing and evaluating a microfluidic chip of BBB model incorporating a real-time monitoring system that combines simultaneous optical and electrical measurements. The device will enable the...

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Direct dies-to-wafer bonding has become, in recent years, a major development axis in microelectronics and at the heart of many LETI projects, both in silicon photonics and for 3D applications involving hybrid bonding. Due to their small size, die bonding allows the study of direct bonding edge effects and the implementation of new direct bonding...

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Discover a unique phd opportunity where you will dive into the heart of innovation in memory technologies. You will develop strong expertise in areas such as electrical characterization and the understanding of degradation phenomena in chalcogenide-based memories. By joining our multidisciplinary teams, you will play a key role in studying and improving the endurance of...

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The development of 4D-STEM (Scanning Transmission Electron Microscopy) has profoundly transformed transmission electron microscopy (TEM) by enabling the simultaneous recording of spatial (2D) and diffraction (2D) information at each probe position. These so-called “4D” datasets make it possible to extract a wide variety of virtual contrasts (bright-field imaging, annular dark-field imaging, ptychography, strain and orientation...

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Cortisol plays a central role in regulating the circadian cycle and in many essential physiological processes such as energy metabolism and immune response. Conventional monitoring of cortisol relies on single blood or saliva samples, which do not accurately reflect the temporal dynamics of its secretion. It is therefore necessary to develop innovative approaches that enable...

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Recently, deep learning has been successfully applied in numerous domains and is increasingly being integrated into healthcare and clinical research. The ability to combine diverse data sources such as genomics and imaging enhances medical decision-making. Access to large and heterogeneous datasets is essential for improving model quality and predictive accuracy. Federated learning is currently developed...

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Fully Homomorphic Encryption (FHE) is a technology that allows computations to be performed directly on encrypted data, meaning that we can process information without ever knowing its actual content. For example, it could enable online searches where the server never sees what you are looking for, or AI inference tasks on private data that remain...

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Phase contrast microscopy and fluorescence microscopy are the two pillars of modern biological imaging. Phase contrast reveals the morphology of the sample, while fluorescent labeling provides specificity to the process of interest. In both cases, the image is the average value of the measured signal. In this thesis, we propose to focus not on the...

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The culture of adherent is a promising approach for various bioproduction applications, such as drug manufacturing and delivery, regenerative medicine, and tracking of cellular differentiation. However, the analysis of single cell morphology and behavior without affecting the substrate integrity remains a major challenge. Lens-free holographic imaging is emerging as a promising solution for real-time, non-invasive...

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Biopharmaceutical production is booming and consists of using cells to produce molecules of interest. To achieve this, monitoring the culture and the state of the cells is essential. Quantitative phase imaging by holography is a label-free optical method that has already demonstrated its ability to measure the concentration and viability of cultured cells. However, implementing...

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The identification of biological material (DNA, RNA, proteins,…) is generally done thanks to cumbersome lab equipment and/or rely on ultra-specific and proprietary sensitive reagents. We aim to develop a new platform based on the solid-state nanopore technology which could produce label-free results on field. One way to pierce a nanopore in an ultra-fine dielectric membrane...

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In the field of high-performance infrared detection, CEA-LETI plays a leading role in the development of the HgCdTe material, which today offers such performance that it is integrated into the James Webb Space Telescope (JWST) and allows the observation and study of deep space with unparalleled precision to date. However, we believe that it is...

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Join CEA-Leti to develop a technological module (localized ground plane) for various applications (EU FDSOI, RF devices, ultra-miniaturized pixels, cryo-RF and quantum). This PhD topic is challenging since you will design step by step a specific module and test it electrically. Our team will support you technically and scientifically to conduct this work. Some data...

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This PhD project focuses on advancing all-solid-state microbatteries for miniaturized energy storage applications, such as wearable electronics, IoT systems, and implantable medical technologies. The research aims to stabilize and mitigate degradation at the electrode/electrolyte interfaces, which are critical bottlenecks in solid-state microbattery performance. The project involves two main research axes: (1) the study and optimization...

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CEA-Leti provides integrated microstorage solutions, including solid state (or solid electrolyte) microbatteries. Solid-state micro-batteries are among the most promising microstorage technologies for applications in several fields such as the internet of things and implantable devices for medical use. The objective of this thesis is to study the impact of mechanical stresses on microbatteries, particularly during...

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The rapid expansion of AI and cloud computing has placed unprecedented demands on data center infrastructure, where energy efficiency is now a defining constraint. Despite their potential, many power systems still rely on silicon-based devices, which suffer from inherent efficiency limitations that result in significant energy losses. GaN HEMTs, with their superior electron mobility and...

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This PhD project aims to develop a mathematical and algorithmic framework for solving acoustic inverse problems in complex environments, based on physics-informed learning. By explicitly incorporating the wave equation into artificial intelligence architectures, the objective is to improve acoustic field reconstruction from partial measurements, the localization of mobile sources, and the quantitative analysis of their...

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Ferroelectric memories of the FeRAM 1T-1C type based on HZO have the potential to replace the last levels of Cache. CEA-Leti is at the state of the art in this field at the 22nm node [1], with 1T-1C bitcells already denser than those of SRAM. In this approach, the selection transistor (1T) is a front-end...

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Are you looking for a PhD at the intersection of acoustics, microsystems, and innovation? This project may be for you.This PhD focuses on the design, fabrication, and experimental validation of an innovative MEMS microspeaker concept based on ultrasound demodulation. Conventional micro transducers face a major limitation: they require large planar surfaces to displace sufficient air...

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Timing is a key function in electronic circuits. Beyond on-chip signals synchronization, it also allows the synchronization of wireless data transmissions. Accurate time references require stable frequency sources, which also benefit to sensor applications. The gold standard for time or frequency generation is still quartz resonators, which are however bulky and difficult to miniaturize. Research...

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The use of direct-conversion detectors in medical radiography opens up new possibilities. Due to its properties, the semiconductor material CdTe has emerged as the material of choice for manufacturing these new components. The proposed thesis topic aims to develop the knowledge and processes necessary to produce CdTe crystals with properties tailored to specific application requirements....

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Modern distributed architectures are becoming increasingly heterogeneous and dynamic, expanding the attack surface and challenging traditional, static security mechanisms. To address these challenges, proactive defense approaches, and particularly Moving Target Defense (MTD), have been introduced to disrupt attackers by regularly modifying the system configuration — for instance, by randomizing network addresses, reallocating containers, or deploying...

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As digital content demand surges, 6G systems face major challenges, particularly in developing power amplifiers for Sub-THz frequencies. These frequencies promise ultra-high data rates but push the limits of current silicon technology. In AI datacenters, optical communication between GPUs is a must to reduce the total energy usage, compared to classical wiring. The highest speed...

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The Information Technology Security Evaluation Facility (ITSEF) conducts activities in the field of security evaluation of electronic systems, embedded software components, either within the framework of certification schemes, for example the one led by the l’Agence Nationale de la Sécurité des Systèmes d’information (ANSSI), or at the direct request of developers. In the context of...

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In many complex environments, such as industrial sites, disaster-stricken buildings, or public spaces, it is necessary to automatically detect and localize sound events (falls, alarms, voices, mechanical failures). Mobile platforms equipped with cameras and microphones represent a promising solution, but a single platform remains limited: its microphone array provides an approximate direction towards the source...

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Technological developments in the electronics sector are experiencing rapid growth, accompanied by increasing interest in accounting for their environmental impacts. However, current approaches remain largely focused on relative impact reductions (energy efficiency, resource optimization), without ensuring compatibility with planetary boundaries. In this context, the concept of absolute sustainability emerges as an essential framework for guiding...

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Medical imaging, a source of major innovations, presents remarkable potential for meeting new challenges with the growing demand for precision medicine, which requires cutting-edge diagnostic and therapeutic approaches personalized for each patient. In this context, CEA-Leti proposes a PhD internship to develop a dedicated preclinical SPECT (Single Photon Emission Tomography) imager that will provide the...

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Chalcogenide materials, particularly Ge-Sb-Te (GST) alloys, are essential for phase-change memory (PCMs). Although high-performance, these memories consume a great deal of energy, which is driving the search for alternative solutions. GST alloys offer unique opportunities in the field of spin-orbitronics as spin-charge conversion materials or as sources of spin-polarized current. Two-dimensional ferromagnetic alloys such as...

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Modern hardware systems, such as RISC-V processors and hardware accelerators, rely on functional simulators and formal verification models to ensure correct, reliable, and secure operation. Today, these models are mostly developed manually from design specifications, which is time-consuming and increasingly difficult as hardware architectures become more complex. This PhD proposes to explore how Large Language...

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For energy reasons, future computers will have to use accelerators for both computation and memory access (GPUs, TPUs, NPUs, smart DMAs). AI applications have intensive computational requirements in terms of both computing power and memory throughput. These accelerators are not based on a simple instruction set (ISA), they break the Von Neuman model: they require...

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The thesis focuses on improving the reliability of deep learning models, particularly in detecting out-of-distribution (OoD) samples, which are data points that differ from the training data and can lead to incorrect predictions. This is especially important in critical fields like healthcare and autonomous vehicles, where errors can have serious consequences. The research leverages vision...

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Critical systems have both functional and timing requirements, the latter ensuring that deadlines are always met during operation; failure to do so may lead to catastrophic consequences. The critical nature of such systems demands specialized hardware and software solutions. This PhD thesis topic focuses on the development of computer architecture designs for critical systems, known...

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Ultrasonic testing (UT) methods are a fundamental component of non-destructive testing (NDT). They are widely used to inspect mechanical components such as welds (in nuclear and petrochemical industries) and composite material structures (in aeronautics). To understand the physical phenomena involved in a given configuration, simulation is a valuable tool and sometimes an essential step in...

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Ultrasonic waves are strongly influenced by the microstructure of the materials through which they propagate, leading to attenuation, dispersion, and noise. Modeling these effects is essential, particularly in non-destructive testing, where they may either hinder defect detection or provide valuable information about the material. Analytical and numerical models help to better predict and interpret these...

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Gold nanoparticles (AuNPs) possess unique electronic, photonic, and chemical properties of invaluable interest in a variety of medical and technological applications. They are typically produced by controlled chemical precipitation from a salt solution to achieve the precise size control critical for most applications. Continuous flow microreactors, which efficiently mix the salt solution and the reducing...

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Generative AI, and particularly language models (LLM), have sparked a new revolution in AI with applications across all domains. However, LLMs are highly resource-intensive and, hence, difficult to implement on autonomous embedded systems. LLMs can be optimized by modifying their architecture to replace heavy Transformer layers with lighter alternatives. Given the difficulty of training LLM...

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Working in a collaborative academic project, your task will be to develop a smart image sensor for a wireless camera network embedding distributed AI computing. Current camera network contains several standard cameras that transmit their images to a global server performing the targeted inference processing. This kind of architecture proposes energy and frugality performances that...

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Halide perovskites (HPs) have demonstrated exceptional potential in photovoltaics (PV), achieving record efficiencies (35% in silicon-based tandem cells). However, their limited stability (degradation under humidity, heat, or light) and scalability challenges (efficiency loss at large scale) hinder industrial adoption. Concurrently, in microLED applications, HPs are emerging as a promising alternative to quantum dots (QDs) for...

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Join CEA-Leti and CROMA to analyze in depth junctions of a new technology. Indeed, our transistors are fabricated under restricted thermal budget for 3D sequential integration, making dopants activation very challenging! Our team will support you technically and scientifically to conduct this work. Some data are already available and waiting for your analysis. During this...

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This PhD aims to investigate and detect backdoor attacks within generative AI model ecosystems, including standalone models, retrieval-augmented generation systems (RAG), and LLM-based agent. The research will focus on developing novel detection and defense mechanisms against stealthy trigger-based attacks, emphasizing real-world deployment scenarios and robust evaluation benchmarks. In addition to developing defense mechanisms and releasing...

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This PhD topic lies within the field of symbolic artificial intelligence. Unlike approaches based on neural networks, these methods rely on explicit rules, often provided by experts or learned from limited data, making them interpretable but potentially imperfect. The central problem is therefore the validation of fuzzy rule bases: the goal is to ensure that...

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In our past studies on SiC power devices, the analysis of electrical performances on diodes [1] (idem for future MOSFETs) must take into account the impact of materialapos;s defects at the epitaxy and substrate level. Initially, the thesis work will consist of setting up tools dedicated to our needs in the SiC team. The specifications...

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This PhD project, conducted on the MAPP platform (CEA-Metz), focuses on the development of additive manufacturing (3D/4D) processes for the integration of smart materials. The aim is to overcome the limitations of traditional planar electronic architectures (PCBs, wafers) integration by enabling the direct-to-shape printing of electronic functions within 3D parts performed by Fused Deposition Modeling...

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This PhD project aims to develop Hopfield-type associative neural networks that perform inference through energy-minimizing dynamics. The goal is to exploit these dynamics for image denoising and reconstruction close to the sensor, under strict energy and latency constraints. The network synapses will be implemented in ReRAM crossbar arrays, enabling analog in-memory matrix-vector operations. The work...

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The SmartCut™ technology is widely used in microelectronics for the fabrication of innovative substrates, such as SOI (Silicon-on-Insulator). The physical phenomena underlying SmartCut™ technology remain one of principal interest of our research. Optimizing the fracture stage is a major focus in our laboratory and in our collaboration with Soitec. Salomonapos;s PhD thesis (expected completion December...

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In our research group we have developed and used during the last few year an innovative technique for frequency generation where the injection locked oscillator are the core. However, this circuits that we found in electronics, but also in other disciplines such as mechanics, biology and fundamental physics, hide still some secrets. In this PhD...

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