Electromagnetic Signature Modeling and AI for Radar Object Recognition
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.
Study of Failure Modes and Mechanisms in RF Switches Based on Phase-Change Materials
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.
Enhanced Quantum-Radiofrequency Sensor
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 capabilities of conventional antenna-based receivers for RF signal detection.
The aim of this thesis is to investigate a hybrid approach to the reception of radio-frequency signals, combining atomic spectroscopy measurement based on Rydberg atoms with the design of a close environment based on metal and/or charged material for shaping and local amplification of the field, whether through the use of resonant or non-resonant structures, or focusing structures.
In this work, the main scientific question is to determine the opportunities and limits of this type of approach, by analytically formulating the field limits that can be imposed on Rydberg atoms, whether in absolute value, frequency or space, for a given structure. The analytical approach will be complemented by EM simulations to design and model the structure associated with the optical atomic spectroscopy bench. Final characterization will be based on measurements in a controlled electromagnetic environment (anechoic chamber).
The results obtained will enable a model-measurement comparison to be made. Analytical modelling and the resulting theoretical limits will give rise to publications on subjects that have not yet been investigated in the state of the art. The structures developed as part of this thesis may be the subject of patents directly exploitable by CEA.
Learning Mechanisms for Detecting Abnormal Behaviors in Embedded Systems
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.
Superconducting Silicon and detection in the far Infrared Universe
Silicon technologies occupy a central position in today’s digital landscape, both for the fabrication of semiconductor devices and for the development of advanced sensors. In 2006, the discovery of superconductivity in silicon heavily doped with boron opened a new field of research. Since then, several laboratories, including CEA, have been investigating its electronic properties and potential applications. This emerging material exhibits particularly attractive characteristics for systems operating at sub-Kelvin cryogenic temperatures, especially in the fields of quantum electronics and ultra-sensitive detectors used in fundamental physics and astrophysics.
Despite these advances, the understanding of superconducting silicon remains incomplete, particularly regarding its thermal, mechanical, and optical properties at the micrometric scale. The proposed PhD aims to address these gaps by combining modelling, design, technological fabrication, and cryogenic characterization of prototype devices, within a close collaboration between CEA-Léti and CEA-Irfu. The main objective will be to develop a new generation of detectors based on this superconducting material and to demonstrate their relevance for the detection of electromagnetic radiation in the terahertz and far-infrared ranges.
Next-Gen Surface Analysis for Ultrathin Functional Materials
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 methodologies for ultrathin oxides and oxynitrides, validate measurement accuracy, and establish robust protocols for quasi in situ transfer of sensitive layers. Applications include advanced CMOS stacks and quantum Josephson junctions, where sub-2 nm AlOx barriers critically determine device performance.
The project directly supports the development of next-generation quantum technologies, advanced photonics and energy-efficient microelectronics by improving the reliability and stability of nanoscale materials. The work will be carried out within a strong multi-partner framework.
Development of a 3D gel dosimetry method for quality control of radiotherapy treatment plans using ultra-high dose rate charged particle beams (FLASH)
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 dosimeters no longer suitable and none of those under development achieving consensus.
The optically read dosimetric gel developed at LNHB-MD (CEA Paris-Saclay) is a promising candidate, as photon beam measurements have shown a linear response over a wide dose range (0.25 - 10 Gy) as well as independence in energy (6 - 20 MV) and dose rate (1 - 6 Gy/min). In addition, this water-equivalent dosimeter has the unique ability to provide three-dimensional measurements with high spatial resolution (< 1 mm) with an associated combined uncertainty of approximately 2% (k = 1). This dosimetry method has been validated for quality control of conventional radiotherapy treatment plans but has never been tested with FLASH beams.
This doctoral project aims to develop a 3D gel dosimetry method suitable for FLASH radiotherapy delivered by charged particle beams: (1) conventional energy electrons (= 10 MeV), (2) very high energy electrons (VHEE = 50 MeV), and (3) protons (= 100 MeV). For each of these types of beams, available at the Institut Curie in Orsay and also at Gustave Roussy in Villejuif, the validation of the dose distribution measured by gel will be carried out by comparison with measurements using other dosimeters (e.g. diamond, alanine) and Monte Carlo simulations.
This study will make a significant contribution to improving patient safety, optimising treatment efficacy and the future integration of FLASH radiotherapy into clinical practice.
Reducing damage and loading in high aspect ratio III-V etching
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: understanding how etching process windows evolve with material loading and process conditions (physical vs. chemical dominance), and minimizing electrical degradation induced by HAR etching, which is critical for device performance.
These challenges are fundamentally linked to the low volatility of In-based etch byproducts, the need to balance kinetic and thermal energy inputs to enhance etch selectivity, and the management of etch loading effects for large-scale production. The experimental approach will leverage CEA-Leti's state-of-the-art facilities, including the Photonics platform for 2–4-inch wafer processing, which enables masking strategies (hard mask deposition, photolithography) and low-temperature (150°C) etching.
Characterization will involve SEM for etch profile analysis, XPS for surface composition, and TEM-EDX for sidewall quality assessment. Damage evaluation will be performed using near-infrared photoluminescence decay to measure minority carrier lifetime and identify recombination centers. The work aims to develop optimized HAR etching processes (aspect ratios >10, critical dimensions <1 µm) for In-based III-V materials, investigate pulsed plasma techniques to reduce etch-induced damage, and provide insights into defect formation mechanisms to guide process optimization for industrial applications.
Introduction of innovative materials for sub-10nm contact realization
As part of the FAMES project and the European ChipACT initiative, which aim to ensure France’s and Europe’s sovereignty and competitiveness in the field of electronic nano-components, CEA-LETI has launched the design of new FD-SOI chips. Among the various modules being developed, the fabrication of electrical contacts is one of the most critical modules in the success of advanced node development.
For sub-10 nm node, the contact realization is facing a lot of challenges like punchthrough (due to low etch selectivity during contact etching), voids during metal deposition, self-alignment, and parasitic capacitance. New breakthrough approach has recently been proposed consisting in the deposition of new dielectric films with chemical gradient. This thesis focuses on the development (deposition an etching processes) of new gradient compounds incorporated into SiO2 to address the current issues.
Advanced characterization of defects generated by technological processes for high-performance infrared imaging
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 degrade sensor performance. Understanding and controlling these defects is essential to increase reliability and optimize processes.
The objective of the thesis is to identify and precisely characterize these defects using cutting-edge techniques, rarely combined, such as Laue microdiffraction and FIB-SEM nanotomography, enabling structural analysis at different scales. By linking the nature and origin of defects to manufacturing processes and quantifying their impact on performance, the doctoral student will contribute directly to improving the reliability and efficiency of next-generation infrared sensors.
The doctoral student will join a team covering the entire detector manufacturing chain and will actively participate in the development (LETI clean room) and structural characterization (CEA-Grenoble platform, advanced techniques) of samples. He/she will also be involved in electro-optical characterization in partnership with the Cooled Infrared Imaging Laboratory (LIR), which specializes in detailed analysis of active materials at cryogenic temperatures.