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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The increasing complexity of heterogeneous networks (satellite, 5G, IoT, TSN) requires an evolution in network management. Intent-Based Networking (IBN), while advanced, still faces challenges in unambiguously translating high-level intentions into technical configurations. This work proposes to overcome this limitation by leveraging Large Language Models (LLMs) as a cognitive interface for complete and reliable automation. This...

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The terahertz (THz) range (0.1–10 THz) is increasingly exploited for imaging and spectroscopy (e.g. security scanning, medical diagnostics, non-destructive testing) because many materials are transparent to THz radiation and have unique spectral signatures. However, existing sources struggle to offer both high power and wide tunability: electronic sources (diodes, QCLs) deliver milliwatts but over narrow bands,...

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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 security assessment of post-quantum cryptography, from the perspective of physical attacks, has been extensively studied in the literature, particularly with regard to the ML-KEM and ML-DSA standards, which are based on Euclidean lattices. Furthermore, in March 2025, the HQC scheme, based on error-correcting codes, was standardized as an alternative key encapsulation mechanism to ML-KEM....

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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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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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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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The performance of micro-LEDs (µLEDs) is crucial for micro-displays, a field of expertise at the LITE laboratory within CEA-LETI. However, simulating these components is complex and computationally expensive due to the incoherent nature of light sources and the involved geometries. This limits the ability to effectively explore multi-parameter design spaces. This thesis proposes to develop...

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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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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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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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Thanks to strong collaborations between teams from several research institutes and the cleanroom facilities at CEA-LETI, Grenoble has been a pioneer in the development of spin qubit devices as a platform for quantum computing. The lifetime of these spin qubits is highly sensitive to fluctuations in the qubitapos;s electrical environment, known as charge noise. Charge...

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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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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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Infertility is a growing problem in all developed countries. The standard methods for the diagnostic of male infertility examine the concentration, motility and morphological anomalies of individual sperm cells. However, 40% of male infertility cases remain unexplained with the standard diagnostic tools. In this thesis, we will explore the possibility to determine the male infertility...

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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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This PhD aims to develop a new class of ultrasonic focusing methods for phased-array imaging by combining deep learning, physics-based modeling, and optimal transport theory. The first research axis introduces a reweighted, probabilistic extension of the Total Focusing Method (TFM), where per-isochrone focusing weights are iteratively estimated by a shared convolutional network and normalized using...

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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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Retinal tears then detachment, a serious eye condition (20–25 cases per 100,000 in France each year), requires urgent surgery. Current treatments involve removing the vitreous, using gas as a tamponade agent, and sealing tears with laser. However, this method presents drawbacks, including patient restrictions (e.g., prolonged lying down) and complications (e.g., cataracts). Injectable hydrogels are...

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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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Clouds are constituted of servers interconnected via the Internet, on which systems can be implemented, making use of applications and databases deployed on the servers. Cloud-based computing is gaining in popularity, and that includes the context of critical systems. As a result, it is useful to define formal frameworks for reasoning about cloud-based systems. One...

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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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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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