Physics-Informed Learning for Acoustic Inverse Problems: Field Reconstruction, Detection, and Detectability Analysis in Complex Environments
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 detectability. The project combines partial differential equation modeling, constrained optimization, and hybrid deep learning. Applications include distributed acoustic sensing systems and the detection of mobile platforms.
Reliability and dynamic properties of GaN high electron mobility transistors : backbarrier and substrate type impact
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 high breakdown voltage, represent a compelling alternative, capable of achieving far higher efficiencies in power conversion. However, their broader adoption is constrained by reliability challenges, particularly those arising from charge trapping mechanisms that degrade device performance over time.
In this PhD project, you will delve into the fundamental dynamics of charge carriers in GaN HEMTs, focusing on the physical origins of on-resistance and threshold voltage drifts—key indicators of device instability. By systematically analyzing the electrical behavior of these transistors under various operating conditions, you will uncover the mechanisms behind their degradation and identify pathways to enhance their robustness. Your findings will directly inform the optimization of device architectures, enabling the development of more efficient and reliable power electronics that can meet the demands of modern data centers and beyond.
You will be part of a multidisciplinary research team at CEA-Leti, collaborating with experts in semiconductor material engineering, device simulation, and electrical characterization. This environment will provide you with a comprehensive skill set, spanning process engineering, advanced electrical testing, and TCAD simulations, This position will not only expand your expertise but also position you at the forefront of a field with global impact. By contributing to the advancement of GaN HEMTs, you will play a key role in shaping the future of power electronics—where innovation directly translates into sustainable technological solutions.
Development of a bifunctionnal zwitterionic nano-coating for aptasensors - a new linker for biological probes that hinders non-specific adsorptions
The field of biosensor development frequently encounters the issue of non-specific signals. These signals often limits the performance of biosensors and complicates industrial transfers. The functionalization steps for biosensors design generally include three steps: i) functionalization of the transducer with a linker molecule, ii) immobilization of a biological probe (antibodies, aptamers, oligonucleotides...) using the linker, iii) treatment with an entity to block non-specific interactions. The literature is full of solutions that highlight the blocking of these non-specific interactions with different types of chemical or biological entities: proteins (BSA, casein...), polymers (PEG, PVP) or small molecules (ethanolamine, hexylamine...).
However, an alternative functionalization approach with a linker that offers both the ability to immobilize biological probes while ensuring the blocking of non-specific interactions represents an innovative path for the development of biosensors.
This PhD project aims to explore the design and surface functionalization with a bifunctional nano-coating responding to this approach. Regarding the blocking, zwitterionic polymers will be at the heart of the development. Indeed, numerous studies demonstrate their ability to drastically reduce the interactions of complex biological environments with surfaces that are functionalized with them. Furthermore, it is possible to exploit the chemical functions of certain types of zwitterions to immobilize biological probes on demand. After optimizing their activity in homogeneous phase, aptamers will be immobilized on silicon transducers (QCM-d and photonic chip) via the bifunctional zwitterionic nano-coating. The objective of the thesis is to obtain a proof of concept of a biosensor functionalized with this new linker that ensures the reduction of non-specific signals while ensuring the specific detection of the target considered (Tyrosinamide model) in model and complex environments derived from biomedical sector, such as serum or plasma.
SiGe HBT LNA for cryogenic applications: design, characterization and optimization
The global race to build a quantum computer is heating up! These cutting-edge systems operate at temperatures below 4 K to preserve the delicate quantum states essential for computation. To achieve efficient control and detection, conventional electronic circuits must perform reliably at cryogenic temperatures, in close proximity to the quantum processor, thereby reducing wiring complexity and boosting performance. Beyond quantum computing, other domains—such as space exploration, high-performance computing, or high-energy physics—also require transistors capable of operating below 100 K.
During this phD, you will perform radiofrequency (RF) electrical characterization and modeling of Silicon-Germanium Heterojunction Bipolar Transistors in cryogenic environment, contributing to a deeper understanding of their behavior and optimizing their potential for extreme-condition applications. The objectives are twofold:
1.RF Electrical Characterization and Modeling:
•Conduct RF electrical measurements of SiGe HBTs at cryogenic temperatures.
•Develop accurate models to describe their behavior in cryogenic environments.
2.Optimization of Low-Noise Amplifiers (LNAs):
•Study the low-temperature behavior of individual passive and active devices composing an LNA.
•Optimize the design of low-noise amplifiers (LNAs) for cryogenic applications.
Study of mechanical stress on Solid State Micro-batteries
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.
Advancing All-Solid-State Microbatteries: Interface Stabilization and Degradation Mitigation for Long-Term Reliability
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.
Advanced SOI technologies: Design, Integration & Electrical characterization
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 are already available and waiting for your analysis.
During this PhD, you will have the opportunity to learn how a module/device is designed step by steps:
From the idea (simulation, bibliography)
Material & Processes understanding (bonding, CMP)
Integration & cleanroom fabrication management
Characterization (physical & electrical: mobility, interface traps)
Valorization (presentations, article)
Study of new photodiode architecture for IR imagers
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 still possible to make a significant step forward in terms of detection performance. Indeed, it seems that a fully depleted structure, called a PiN photodiode, could further reduce the dark current (and thus reduce noise and gain sensitivity at low photonic flux) compared to the non-fully depleted structures currently used. This architecture would represent the ultimate photodiode and would allow either a further increase in performance at a given operating temperature or a significant increase in the operating temperature of the detector, with the potential to open new fields of application by greatly simplifying cryogenics.
Your role in this thesis work will be to contribute to the development of the ultimate photodiode for very high-performance infrared detection, characterize and simulate the PiN photodiodes in HgCdTe technology manufactured on our photonic platform.
Candidate Profile:
You hold a Master's degree in optoelectronics and/or semiconductor material physics and are passionate about applied research.
The main technical skills required are: semiconductor component physics, optoelectronics, data processing, numerical simulations, interest in experimental work to carry out characterizations in a cryogenic environment but also theoretical work to carry out numerical simulations.
The PhD student will be integrated into a multidisciplinary team ranging from the growth of II-VI materials to electro-optical characterization, including microelectronics manufacturing processes in clean rooms and the packaging issues of such objects operating at low temperature.
High-Endurance Chalcogenide Memories for Next-Generation AI
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
Dies to wafer direct bonding: from physical mechanisms to the development of thin stackable dies
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 processes that can shed original light on the mechanisms of direct bonding, which are already well studied at LETI. From a more technological perspective, the development of thin stackable chips will also be a very interesting technological key for many applications. This approach is a clever alternative to classical damascene processes to address the challenges related to the planarization of surfaces with low density of high topographies.