RSS export of vacancies - Only featured vacancies : No / Profile : Physique théorique, Défis technologiques

SL-DRT-26-0722 - Systemic validation of fuzzy rule bases: accounting for data availability and the specific characterist

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 the rules produce consistent, useful, and reliable results. Existing methods use global metrics (overall system performance) and local metrics (the quality of each rule), but they do not sufficiently account for certain important specificities. For example, interactions between rules can strongly influence the final behavior. The thesis proposes to develop a comprehensive and systematic approach to validate these rule bases, whether data is available or not. In particular, it aims to design new metrics capable of capturing these interactions, drawing inspiration, for example, from graph-based approaches (such as FinGrams or reputation systems). The work will include the definition of a methodological framework, the proposal of new validation measures, as well as their implementation and experimental evaluation. The expected outcomes are more precise tools for detecting problematic rules, and an overall improvement in the performance and reliability of fuzzy inference systems.

Systemic validation of fuzzy rule bases: accounting for data availability and the specific characteristics of fuzzy inference

SL-DRT-26-0708 - Low Power Image Sensor for Distributed Processing in Cameras Network

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 are not compatible with IoT requirements. The project goal is to tackle hardware frugality through a distributed and collaborative approach based on ultra-low-power computing nodes. Each node’s inference core will be built around ASIC processors performing calculations in analog form. The final demonstrator will consist of a wireless network of “motes” (sensor network nodes) integrating dedicated image sensors paired with hybrid processors performing analog processing. In this context, the mote’s image sensor must extract strategic features with frugality and efficiency which implies that you have to define, design and test an innovative readout architecture of a standard imager. In collaboration with the academic partners, you will be involved in the definition of the overall mote architecture allowing to define basically the output data format and the output procedure of the imager including potential pre-processing for the distributed inference computations. The studied architecture will integrate innovative low power solutions to address the targeted IoT applications and perform both image acquisitions and AI pre-processing. As an image sensor demonstrator is planned in this PhD Thesis, the work will be conducted at CEA-Leti in the L3i Laboratory, using professional IC design tools and software development environments.

Low Power Image Sensor for Distributed Processing in Cameras Network

SL-DRT-26-0758 - How defects nucleation affects the the fracture on the SmartCut process

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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. Salomon's PhD thesis (expected completion December 2026), the development of post-fracture surface analysis protocols highlighted the link between the evolution of cristalline defects that cause fracture (platelets) and post-fracture surface roughness. We were thus able to characterize the early stages of platelet growth and determine their main characteristics (size and density). This had previously only been achieved through complex characterizations based on TEM observations. Now that we have highlighted the impact of platelets on post-fracture surface roughness, the next step is to investigate and identify ways to control their nucleation using new processes. This will also involve optimizing the post-fracture state of SOI substrates.

How defects nucleation affects the the fracture on the SmartCut process

SL-DRT-26-0763 - AI model deployment using Hardware-Aware on-chip Fine Tuning

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
Emerging unconventional hardware technologies are essential for future Edge-AI applications, but they often suffer from variability, mismatches, and technology dispersion. These non-idealities can strongly reduce AI inference accuracy if no fine-tuning or calibration is applied. Traditional supervised fine-tuning is difficult to industrialize because it raises issues related to data confidentiality, service quality, software complexity, and hardware constraints. This PhD project aims to develop hardware-algorithm co-design methods that avoid the need for fully supervised on-chip retraining. The main goal is to create task-agnostic, inference-level self-calibration strategies able to compensate hardware mismatches at the system level. The work will study existing adaptation methods, including weight-based, feature-based, output-based, and domain adaptation approaches. The project will define a relevant Edge-AI application, develop a generic fine-tuning method, and validate it through low-level electrical simulations. If possible, the proposed algorithm may also be tested experimentally on a custom ASIC-based hardware setup.

AI model deployment using Hardware-Aware on-chip Fine Tuning

SL-DRT-26-0730 - Junction defect characterization of low therMal Budget SOI MoSFET

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 PhD, you will have the opportunity to perform all theses steps: From the idea (simulation, bibliography, TCAD) 20% Processes understanding (implantation, SPER) 10% Integration & cleanroom fabrication management 10% Characterization (physical & electrical: noise, DLTS…) 50% Valorization (presentations, article) 10% This PhD offers a unique chance to be at the forefront of technological innovation and to make a significant impact in the field of advanced SOI. Join us and take the first step towards an exciting career in research and development! With a background in microelectronics or nanotechnologies, you are curious about integration of new processes, not afraid about equations and liked semiconductors classes at school. You want to solve complex puzzles and enjoy collaborating with others to figure out innovative solutions.

Junction defect characterization of low therMal Budget SOI MoSFET

SL-DES-26-0670 - Dual Active Bridge Topology Based on SiC Synthetic Switches for Ultra-Fast Active Stabilization of a Low

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
With the massive deployment of direct current (DC) technologies on the grid, particularly photovoltaics and grid-connected battery energy storage systems (BESS), a growing share of electrical energy now flows through static power converters. Unlike classical grids dominated by rotating machines, which benefit from high natural inertia, power-electronics-dominated networks exhibit very limited inertia and may therefore experience highly dynamic voltage spikes, voltage drops, or even complete collapse. Some research focuses on synthetic inertia, emulated through specific control strategies implemented in static converters, but these approaches depend on equipment manufacturers and do not rely on established standardization. Another approach consists in designing dedicated equipment specifically intended for the active stabilization of low-inertia power systems, which is the direction explored in this PhD project. A particularly demanding case concerns MVDC grids, which by construction rely entirely on static power converters, therefore exhibiting extremely low natural inertia, and requiring the use of converters based on specific technologies. Within the framework of this PhD, we propose the study and proof of concept of a converter connected to an MVDC electrical network operating between 6 and 12 kV, capable of injecting or absorbing very high levels of power in a transient manner, on the order of ten megawatts for durations ranging from 10 µs to 100 ms. The system will rely on an isolated Dual Active Bridge (DAB) topology, with a medium voltage capacitive DC bus at its primary. This power electronics topic presents several technological bottlenecks. Synthetic switches (series-connected SiC devices, as investigated in a previous PhD in the laboratory) will have to be implemented in a real DAB converter. A highly isolated power supply for the gate drivers of these synthetic switches will need to be designed. The medium-frequency DAB transformer must be designed to transfer very high transient power while minimizing volume. Particular attention will therefore be paid to transient-oriented design, with the objective of identifying the key parameters that maximize, within a complex structure, the ratio between the converter rated power and its peak power. Potential extensions toward other pulsed-power applications that could benefit from such a converter will be explored, taking into account their specific constraints.

Dual Active Bridge Topology Based on SiC Synthetic Switches for Ultra-Fast Active Stabilization of a Low-Inertia Converter-Dominated DC Grid.

SL-DRT-26-0656 - Topologically Isolated Mode Acoustic Resonators

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 is therefore still ongoing to provide high quality factor (> 10,000) resonators, ideally capable of operating at frequencies of several GHz. A key to reach such high quality factors is to confine strongly the mechanical vibration of micro-size structures in order to make them insensitive to external perturbations. Recently, the field of topological acoustics has demonstrated the capability to confine elastic waves in very small volumes concentrated at the interface between periodic structure, and to provide extremely high quality factor resonances. This PhD position focuses on exploiting topologically protected modes in piezoelectric microstructures to provide next generations of high quality factor resonators, which may be used in oscillators or even filter circuits. Leveraging the know-how of CEA Leti in the design and fabrication of such components, the PhD will be part of an international collaboration with well established academic laboratories (Politecnico di Milano, Imperial College FEMTO-ST Institute) and industrial partners. The candidate will model and design structures supporting topologically protected modes, combinining finite element simulations with simplified numerical approaches which reduce computation times. He will follow the fabrication of demonstrators in collaboration with the process integration teams in the CEA Leti clean rooms, and carry on measurements of the proposed resonators.

Topologically Isolated Mode Acoustic Resonators

SL-DES-26-0651 - Intelligent control and optimization of DC microgrids using digital twins in real-time simulation

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
This thesis addresses the challenge of decarbonizing industrial and territorial systems by proposing a transition to direct current (DC) microgrids controlled by a Digital Twin. Faced with the saturation of alternating current (AC) grids due to the growth of photovoltaics, energy storage, and electric mobility, DC allows for a reduction in conversion losses (5 to 15%), improved flexibility, and a simplification of the electrical architecture. The project is based on the development of a high-fidelity Digital Twin synchronized in real-time simulation. More than just a monitoring tool, it acts as a proactive decision-making system integrating advanced optimization algorithms, such as artificial intelligence and predictive control. It anticipates voltage instabilities, which are particularly critical in low-inertia DC grids, and continuously optimizes power flows to maximize self-consumption while preserving battery life. Experimental validation relies on a Hardware-in-the-Loop approach within the CEA-Liten/G2Elab ecosystem, integrating physical converters. This methodology guarantees robustness, security, and resilience before any real-world deployment. The expected outcomes are scientific (stability and real-time modeling), operational (provision of technical guides and decision-making tools), and strategic (strengthening French technological sovereignty in Smart Grids and accelerating the 2050 carbon neutrality trajectory advocated by ADEME).

Intelligent control and optimization of DC microgrids using digital twins in real-time simulation

SL-DRT-26-0658 - Multi-scale approach for ultrasonic propagation in inhomogeneous multiple-scattering media

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 phenomena. Homogeneous statistical properties are generally assumed in such approaches. In practice, however, microstructures often exhibit significant spatial variations, for instance due to manufacturing processes. Depending on the scale of these variations relative to the wavelength, they may induce either abrupt or gradual changes in effective properties. This PhD aims to establish a theoretical framework that accounts for both microstructural randomness and its spatial variations, in order to propose relevant simulation strategies depending on the scales involved. The approach will first be developed in 1D, then extended to 2D and 3D using tools developed in the laboratory, with numerical and possibly experimental validations.

Multi-scale approach for ultrasonic propagation in inhomogeneous multiple-scattering media

SL-DES-26-0641 - Potential synergy between NH3 and NaBH4 for improved H2 density and enhanced safety

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
The thesis focuses on the study of the hybrid ammonia–sodium borohydride system (NH3–NaBH4) as an innovative chemical energy carrier. The objective is to investigate the combination of ammonia (NH3), recognised for its high hydrogen density and mature industrial infrastructure, with sodium borohydride (NaBH4), a high-capacity chemical hydrogen storage material, in order to overcome certain limitations associated with each vector when considered separately. The proposed work specifically addresses the safer storage and transport of ammonia through its coupling with sodium borohydride, enabling a reduction in vapour pressure (compared to 8.88 bar at 21 °C for liquid ammonia) and less restrictive operating conditions. In parallel, the thesis aims to improve the stability (relative to the H2O–NaBH4 system) and operability of sodium borohydride which, when combined with ammonia molecules (acting as inert species), forms stable liquid or viscous phases that are potentially pumpable, thereby facilitating integration into energy-related processes. The fundamental goal of the thesis is to understand the physicochemical mechanisms governing this hybrid system, particularly the role of dihydrogen interactions between the N–H bonds of ammonia and the B–H bonds of borohydride, and their influence on stability, reactivity, transport properties, and hydrogen release pathways (thermal and/or hydrolytic). Beyond its storage function, the thesis also explores the potential of the NH3–NaBH4 system as a novel hybrid material with high gravimetric and volumetric hydrogen capacity, while considering realistic operational constraints relevant to energy applications in a dual-use context. At this stage, exhaustive optimisation is not the primary objective.

Potential synergy between NH3 and NaBH4 for improved H2 density and enhanced safety

SL-DRT-26-0635 - High-Endurance Chalcogenide Memories for Next-Generation AI

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 Phase-Change Memory (PCM) and Threshold Change Memory (TCM) devices—two promising technologies for high-performance artificial intelligence applications. You will take part in innovative projects combining scientific rigor and applied research on nanoscale devices, working closely with another CEA PhD student who conducts advanced physico-chemical analyses (TEM) to investigate degradation mechanisms. You will have the opportunity to contribute actively to tasks such as: Electrical characterization of PCM and TCM devices to analyze cycling-induced degradation Development and evaluation of innovative programming protocols to extend endurance limits Proposing solutions to improve the reliability and performance of next-generation memories Regular collaboration and discussion with the CEA PhD student to interpret TEM results and draw conclusions about degradation mechanisms

High-Endurance Chalcogenide Memories for Next-Generation AI

SL-DRT-26-0626 - Ultra-low frequency wireless power transmission for sensor node charging

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 significantly limits their adoption in complex environments (industrial, biomedical, etc.).The ultra-low-frequency technology investigated in our laboratory is based on an electromechanical receiver system comprising a coil and a magnet set into motion by a remotely generated magnetic field. The objective of this PhD project is to propose and develop novel ultra-low-frequency concepts to increase transmission range while maintaining sufficient power density for supplying sensor systems. The work will therefore involve studying, designing, optimizing, and experimentally validating the performance of new topologies (emitter field shaping, receiver geometries and materials, etc.). The candidate will develop analytical and numerical models to identify key system parameters and compare performance with the state of the art (range, power density, sensitivity to orientation). In addition, the candidate will propose, design, and experimentally evaluate innovative energy conversion electronics, on the transmitter and/or receiver side, to assess their impact on the overall system performance. A joint optimization of the electromechanical system and its associated power electronics will ultimately lead to the realization of a high-performance wireless power transfer system. A multidisciplinary profile with a strong orientation toward physics and mechatronics is sought for this PhD project. In addition to solid theoretical foundations, the PhD candidate must demonstrate the ability to work effectively in a team environment as well as a strong aptitude for experimental work. The PhD candidate will be integrated into the Systems Department of CEA-Leti, within a team of researchers with strong expertise in the development and optimization of electronic and mechatronic systems, combining innovative solutions for energy harvesting, wireless power transfer, low-power electronics, and sensor integration aimed at the development of autonomous systems.

Ultra-low frequency wireless power transmission for sensor node charging

SL-DRT-26-0631 - Sofware support for computing accelerators and memory transferts accelerators

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 specialized code to be written manually. Furthermore, it is difficult to compare the use of these accelerators with code using a non-specialized processor, as the initial source codes are very different. HybroLang is a hardware-close programming language that allows programs to be written using all of a processor's computing capabilities, while also allowing code to be specialized based on data known at runtime. The HybroGen compiler has already demonstrated its ability to program in-memory computing accelerators, as well as to optimize code on conventional CPUs by performing innovative optimizations. This thesis proposes to extend the HybroLang language in order to - facilitate the programming of AI applications by providing support for complex data: stencils, convolution, sparse computing - enable code generation both on CPUs and with hardware accelerators currently under development at the CEA (sparse computing, in-memory computing, memory access) - allow to benchmark different computing architectures with the same initial source code Ideally, a candidate should have knowledge of computer architecture, programming language implementation, code optimization and compilation.

Sofware support for computing accelerators and memory transferts accelerators

SL-DRT-26-0606 - Learning Mechanisms for Detecting Abnormal Behaviors in Embedded Systems

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 system's state is becoming necessary to detect an attack before its impacts become harmful. The IDS that interest us are based on machine learning anomaly detection methods and allow learning the normal behavior of a system and raising an alert at the slightest deviation. However, the learning of normal behavior by the model is done only once beforehand on a static dataset, even though the embedded systems considered can evolve over time with updates affecting their nominal behavior or the addition of new behaviors deemed legitimate. The subject of this thesis therefore focuses on studying re-learning mechanisms for anomaly detection models to update the model's knowledge of normal behavior without losing information about its prior knowledge. Other learning paradigms, such as reinforcement learning or federated learning, may also be studied to improve the performance of IDS and enable learning from the behavior of multiple systems.

Learning Mechanisms for Detecting Abnormal Behaviors in Embedded Systems

SL-DRT-26-0614 - Optimized control of a modular energy hub with minimal EMC signature

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 (PV) system, an electric vehicle, a grid, and stationary storage with loads. The main objective of this thesis is to improve the efficiency, compactness, and modularity of the energy hub through control. Several ideas emerge to achieve this, such as advanced control to minimize losses, the use of AC input opposition to reduce electromagnetic compatibility (EMC) filtering, series/parallel DC output configurations to address 400Vdc/800Vdc batteries, and increasing the switching frequency to reduce volume, etc. Thus, this thesis will, in the medium term, lead to the development of an optimal converter in terms of both energy efficiency and environmental impact.

Optimized control of a modular energy hub with minimal EMC signature

SL-DRT-26-0633 - Study of mechanical stress on Solid State Micro-batteries

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 microbattery charge/discharge cycles. To this end, two approaches will be considered: experimental study with the development of mechanical test benches and numerical simulation. The PhD student's work will begin with the development of test benches, the first of which will apply variable pressure to the surface of a microbattery during charge/discharge cycles. He/she will be required to develop the pressure measurement equipment. Once the mechanical test bench is operational, other characterizations, such as measuring anode deformations, will be considered. In parallel with this experimental work, a mechanical model will be developed. This model will be progressively refined using the experimental results obtained with the mechanical test bench, and new characterizations may be implemented in order to obtain the mechanical properties of the different materials used. Ultimately, the objective will be to propose the integration of new layers to improve the mechanical performance of microbatteries during cycling.

Study of mechanical stress on Solid State Micro-batteries

SL-DRT-26-0613 - CdTe for medical radiography; control of electrical properties

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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. The work will draw on the laboratory’s advanced expertise in mastering CdTe single-crystal growth processes. The key challenges of the project will be as follows: - Performing annealing under controlled atmospheres (ex-situ, on small samples) to study their impact on the electrical properties of CdTe, - Conducting advanced characterizations to better understand the doping mechanisms in CdTe, - Fabricating “simple” devices and testing them under X-ray flux to quantify the performance of the laboratory’s materials. The proposed thesis topic is central to the development of a CdTe technology for medical radiography applications. Multidisciplinary work (material and process development, material characterization, fabrication and X-ray testing of simplified devices) is proposed to address this topic.

CdTe for medical radiography; control of electrical properties

SL-DRT-26-0632 - Advancing All-Solid-State Microbatteries: Interface Stabilization and Degradation Mitigation for Long-Te

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 of ultrathin films (sub-nanometer to nanometer scale deposited by ALD) for engineering the interfaces in LiCoO2/LiPON/Li stacks, and (2) a fundamental investigation of the mechanisms responsible for interface degradation. The study will involve the fabrication and characterization of partial and complete stacks using techniques like cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The incorporation of alloying metals (e.g., Ag, Au) between the buffer layer and lithium will also be explored to enhance lithium-metal interface stability. The expected outcomes include an optimized microbattery stack capable of exceeding 1,000 cycles with minimal increase in interfacial resistance and a comprehensive framework describing degradation mechanisms and buffer layer effects.

Advancing All-Solid-State Microbatteries: Interface Stabilization and Degradation Mitigation for Long-Term Reliability

SL-DRT-26-0597 - Electromagnetic Signature Modeling and AI for Radar Object Recognition

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
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 & Propagation Laboratory at CEA-LETI, Grenoble (France), a world-class research environment equipped with state-of-the-art tools for propagation channel characterization and modelling. A collaboration with the University of Bologna (Italy) is planned during the PhD. This PhD thesis aims to develop advanced electromagnetic models of near-field radar backscattering, tailored to radar and Joint Communication and Sensing (JCAS) systems operating at mmWave and THz frequencies. The research will focus on the physics-based modeling of the radar signatures of extended objects, accounting for near-field effects, multistatic and multi-antenna configurations, as well as the influence of target materials and orientations. These models will be validated through electromagnetic simulations and dedicated measurement campaigns, and subsequently integrated into scene-level and multipath propagation simulation tools based on ray tracing. The resulting radar signatures will be exploited to train artificial intelligence algorithms for object recognition, material property inference, and radar imaging. In parallel, physics-assisted AI approaches will be investigated to accelerate electromagnetic simulations and reduce their computational complexity. The final objective of the thesis is to integrate radar backscattering-based information into a 3D Semantic Radio SLAM framework, in order to improve localization, mapping, and environmental understanding in complex or partially obstructed scenarios. We are seeking a student at engineering school or Master’s level (MSc/M2), with a strong background in signal processing, electromagnetics, radar, or telecommunications. An interest in artificial intelligence, physics-based modeling, and numerical simulation is expected. Programming skills in Matlab and/or Python are appreciated, as well as the ability to work at the interface between theoretical models, simulations, and experimental validation. Scientific curiosity, autonomy, and strong motivation for research are essential.The application must include a CV, academic transcripts, and a motivation letter.

Electromagnetic Signature Modeling and AI for Radar Object Recognition

SL-DRT-26-0602 - Study of Failure Modes and Mechanisms in RF Switches Based on Phase-Change Materials

Tue, 23 Jun 2026 02:15:48 Z

Category : Technological challenges
Contract : Thèse
Thesis topic details :
Switches based on phase change materials (PCM) demonstrate excellent RF performance (FOM <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 of these failures are not discussed. The objective of this thesis will therefore be to study the failure modes and mechanisms for different operating conditions (endurance, hold, power). The analysis will be carried out through electrical and physical characterizations and accelerated aging methods will be implemented.

Study of Failure Modes and Mechanisms in RF Switches Based on Phase-Change Materials