Clean Room Activity Simulation Tool Development
During a previous internship, a tool for simulating batch execution in a clean room was developed. This tool takes into account processing times on equipment, equipment failures, and certain holds related to integration. The batches injected into this simulator come from the actual history of the clean room.
The goal of the PhD is to develop a simulator that can prospectively simulate batch execution based on the POR routes of the main themes present or upcoming in the clean room. Based on the POR routes, the tool should be able to generate development batches for technology bricks (short loops), as well as functional batches including test plates and pilot plates. A nomenclature and enrichment of the routes through metadata will need to be carried out to enable the tool to generate batches realistically, both in terms of process and project scheduling.
Different simulation engines will be compared in terms of performance and accuracy. Classical resolution engines (discrete simulation, event-driven, conjunctive graph-based) as well as innovative approaches (primarily reinforcement learning, but also supervised learning) will be studied.
The development and publication of a methodology for creating simulation instances (testbed) will also be carried out during this PhD work.
Development of vertical GaN power transistors gate module
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 career!
Vertical GaN power components are highly promising for applications beyond the kV range and are therefore extensively studied worldwide. Transistors with a 'trench MOSFET' architecture have been demonstrated in the state-of-the-art with very encouraging results. The gate stack of these devices is a crucial element as it directly impacts their on-state resistance, threshold voltage, and the control signal to be applied in a power converter. The proposed study will focus on developing innovative gate stacks that can withstand high gate voltages while maintaining state-of-the-art threshold voltage and channel mobility with minimal gate dielectric trapping. The work will involve studying the impact of process parameters on electrical characteristics. Special attention will be given to optimizing the gate geometry through TCAD simulations to study how its shape impacts on-state and breakdown. Identified improvements will be integrated to the devices fabricated on our 200mm GaN power devices line. The work will take place within the power devices lab and will be supported by several ongoing projects.
Study of Etching Mechanisms in Dielectric Materials: Application to Low Global Warming Potential Gases
Interconnection levels (Back-End Of Line, or BEOL) in microelectronics enable the connection of transistors to achieve the desired device functionalities. The fabrication of these levels relies on lithography and plasma etching processes. Plasma dry etching is a key technique in the manufacturing of microelectronic devices, as it allows the precise definition of structures at the nanometer scale. This process involves several major challenges, including stringent control of etch profiles, critical dimensions of the patterns, and the assurance of selectivity between different materials. Beyond these technical aspects, plasma etching also raises significant environmental concerns. Indeed, the gases used in these processes, such as fluorocarbons, are often greenhouse gases with very high global warming potential (GWP).
The objective is therefore twofold: to reduce the carbon footprint of these processes while maintaining, or even improving, the critical post-etch performance metrics, such as achieving the target critical dimensions, avoiding damage to the etched materials, preventing defect formation, and ensuring the spatial uniformity of these performances
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.
Integrated optical functions on microbolometer focal planes for uncooled infrared imaging
Thermal infrared imaging (wavelengths 8-14 µm) is a growing field, particularly in industry, transportation, and environment. It relies on a detection technology, microbolometers, for which CEA-Leti is at the forefront of the global state of the art. Integrating advanced optical functions directly onto the detectors is a very promising approach for improving performance, compactness, and cost in future infrared cameras.
The optical functions under consideration include spectral filtering, polarimetry, wavefront correction, and more. Some aim to enrich the image with information essential for applications such as absolute thermography (temperature and emissivity measurement), identification for automated scene interpretation (machine vision), gas detection, and others.
The proposed work will include the design, fabrication, and electro-optical characterization of functionalized microbolometer arrays. Using 3D electromagnetic simulation tools, the design of these optical functions will take into account the compatibility with our microbolometer technologies and the capabilities of our microfabrication facilities. Fabrication will take place in the CEA-Leti cleanrooms by dedicated personnel, but the candidate will participate in defining and monitoring the work. Finally, optical and electro-optical characterizations will be performed in our laboratory, if necessary with the development of dedicated characterization benches.
GPU-ACCELERATED CHARACTERISTICS METHOD FOR 3D NEUTRON TRANSPORT COMBINING THE LINEAR-SURFACE METHOD AND THE AXIAL POLYNOMIAL EXPANSION
This thesis falls within the framework of advancing numerical computation techniques for reactor physics. Specifically, it focuses on the implementation of methods that incorporate higher-order spatial expansions for neutron flux and cross-sections. The primary objective is to accelerate both existing algorithms and those that will be developed through GPU programming. By harnessing the computational power of GPUs, this research aims to enhance the efficiency and accuracy of simulations in reactor physics, thereby contributing to the broader field of nuclear engineering and safety.
Adaptive Orchestration for Proactive Security in Distributed Systems
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 decoy services. However, most existing strategies remain static, rely on a single defense mechanism, and ignore the underlying hardware state. In parallel, hardware-level countermeasures such as cache partitioning, randomization, and scheduling have been proposed against side-channel attacks, yet they are seldom integrated into the decision logic of orchestration frameworks.
The objective of this PhD is to design an adaptive MTD orchestration framework that is aware of the underlying hardware state, capable of dynamically adjusting defense strategies according to system load, performance, and observed vulnerability. The central idea is to feed a reinforcement learning (RL) agent with information derived from hardware performance counters and local security metrics linked to shared cache dynamics, enabling it to select the optimal combination of MTD strategies based on the current system context.
The expected contributions include the definition of a hardware-informed local security metric capturing cache behavior, the graph-based modeling of dependencies between services, resources, and attack surfaces, the design of a unified RL-based decision agent for adaptive MTD selection, and a multi-criteria evaluation (security, performance, energy) on a realistic automotive use case.
This thesis aims to bridge system-level and hardware-level perspectives to build trustworthy orchestrators capable of anticipating and adapting defenses against evolving threats, paving the way toward intelligent and hardware-aware proactive security in distributed systems.
Innovative techniques for evaluating critical steps and limiting factors for batteries formation
The battery manufacturing sector in Europe is currently experiencing strong growth. The electrical formation step that follows battery assembly and precedes delivery has received little academic attention, despite being crucial for battery performance (lifespan, internal resistance, defects, etc.). It is an essential time-consuming and costly step in the process (>30% of the cell manufacturing cost, and 25% of the equipment cost in a Gigafactory) that would greatly benefit from optimization.
In this thesis, we propose studying battery formation using innovative, complementary, operando non-intrusive techniques. The goal is to identify the limiting mechanisms of the electrolyte impregnation step (filling electrode pores) and of the initial charge. The candidate will implement experimental methods to monitor and analyze these mechanisms. He will also establish a methodology and protocols for studying these steps, combining electrochemical measurements with non-intrusive physical characterizations under operating conditions. The research will focus on optimizing formation time and quality control during this stage.
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.
Simulation of nuclear glass gels at the mesoscopic scale using a quaternary system.
This research work is part of studies conducted on the long-term behavior of nuclear glass used to immobilize radioactive waste and potentially intended for geological disposal. The challenge lies in understanding the mechanisms of alteration and gel formation (a passivating layer that can slow down the rate of glass alteration) by water and in predicting the kinetics of radionuclide release over the long term.
The proposed simulation approach aims to predict, at a mesoscopic scale, the maturation process of the gel formed during the alteration of glass by water using a ternary “phase field model” composed of silicon, boron, and water (leachate), to which aluminum will be added.
The underlying quaternary mathematical model will consists of a set of coupled nonlinear partial differential equations. These are based on Allen-Cahn and transport equations. The numerical solution of the associated equations is performed using the Lattice Boltzmann Method (LBM) programmed in C++ in the massively parallel LBM_saclay calculation code, which runs on several HPC architectures, both multi-CPUs and multi-GPUs.
The proposed research requires a solid foundation in applied mathematics and programming in order to develop the algorithms necessary for the correct resolution of the new system of strongly coupled equations.