Vertical GaN power devices development using localized epitaxy
This PhD 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 materials 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 hold great promise for power applications beyond the kV range. Localized epitaxy of GaN enables the creation of thick structures on Si substrates at a competitive cost, with demonstrated success for diodes and pseudo-vertical transistors. However, this approach’s significant surface area limits the energy density of the devices. This PhD aims to develop denser, fully vertical components using layer transfer methods. You’ll study their electrical characteristics to monitor the impact of technological variations on their performance.
Throughout this PhD, you’ll gain comprehensive knowledge in microelectronics processes, electrical characterization, and TCAD (Technology Computer-Aided Design) simulation. You’ll collaborate with a multidisciplinary team including our partner CNRS-LTM and deepen your understanding of GaN power devices, all while being part of a lab dedicated to the development of wide-bandgap power devices. You will have the opportunity to write publications and patents.
Optimizing cryogenic super-resolution microscopy for integrated structural biology
Super-resolution fluorescence microscopy (“nanoscopy”) enables biological imaging at the nanoscale. This technique has already revolutionized cell biology, and today it enters the field of structural biology. One major evolution concerns the development of nanoscopy at cryogenic temperature (“cryo-nanoscopy”). Cryo-nanoscopy offers several key advantages, notably the prospect of an extremely precise correlation with cryo-electron tomography (cryo-ET) data. However, cryo-nanoscopy has not provided super-resolved images of sufficiently high quality yet. This PhD project will focus on the optimization of cryo-nanoscopy using the Single Molecule Localization Microscopy (SMLM) method with fluorescent proteins (FPs) as markers. Our goal is to significantly improve the quality of achievable cryo-SMLM images by (i) engineering and better understanding the photophysical properties of various FPs at cryogenic temperature, (ii) modifying a cryo-SMLM microscope to collect better data and (iii) developing the nuclear pore complex (NPC) as a metrology tool to quantitatively evaluate cryo-SMLM performance. These developments will foster cryo- correlative (cryo-CLEM) studies linking cryo-nanoscopy and cryo-FIB-SEM-based electron tomography.
Simulation and characterization of integrated structures during and after the millisecond laser annealing step
Laser annealing processes are now used in a large range of applications in most advanced microelectronics technologies. Whether in the context of advanced planar CMOS components or 3D integration technologies, the specific characteristics of laser annealing enables to reach very high temperatures in very short times, at die scale, and to work in conditions out of thermodynamic equilibrium. This has many advantages in terms of physical effects (activation of high dopants with low diffusions, transformation of silicides, etc.), but also thermal budget (high temperatures which remain on the surface of the material). However, this kind of ultrashort optical annealing can generate pattern effect temperature variations on the chip surface between two zones with different radiative andor thermal properties. These temperature differences may alter the electrical performances of the devices and thus have to be evaluated and overcome. A part of this work will consist, by the help of bibliography study, in finding integrative solutions (design, absorbent layer,…), in order to encounter this issue. Besides, at LETI, a wide knowledge of Nanosecond Laser Annealing (NLA) is in place for many years, and process teams are in the acquisition phase of a millisecond laser equipment (DSA). This work will represent, thanks to the numerical simulation, one of the essential building blocks for the development of the millisecond laser annealing at LETI which is mandatory for advanced technologies roadmap.
This interdisciplinary research will encompass fields such as numerical simulations, materials science, microelectronic manufacturing processes. You will benefit from the support of laboratories specializing in integration processes, as well as TCAD simulation environments.
Selective epitaxial Regrowth for extended Base contact in High-Performance Antimonide-based HBT Transistors
With the rapid expansion of wireless networks and the imminent arrival of 6G, the need for highly efficient communication systems has never been more critical. In this context, frequencies beyond 140 GHz emerge as a key frontier, where cutting-edge technologies leverage advanced semiconductors like InP, delivering unmatched performance beyond what SiGe solutions can achieve. However, III-V components remain expensive, manufactured on small substrates (100 mm for InP), and incompatible with silicon production lines, which ensure higher industrial yields.
In this context, CEA-LETI, in collaboration with CNRS-LTM, is developing a new HBT transistor technology in which the base layer is made of antimonides, having already demonstrated frequency performance beyond the THz range. To enable integration with Si-CMOS fabrication processes, a novel approach for ohmic contact formation is required. This involves selective epitaxial regrowth of a suitable semiconductor material on the base layer of the HBT-GaAsSb transistor.
The PhD candidate will be responsible for identifying the optimal material that meets the required criteria, based on experiments conducted with the epitaxy team, advanced physical characterizations (ToF-SIMS, HR-TEM, EDX), and band structure modeling of the formed heterojunctions. This research will also be complemented by the fabrication of technological test structures to extract the key electrical parameters necessary for optimizing the DC and RF performance of the HBT transistor.
Towards a Sustainable Blockchain: Reducing Energy Consumption While Ensuring Security and Integrity
Blockchain technology, a key component of distributed ledger systems, enables decentralized digital interactions without the need for a central authority but raises environmental concerns due to its energy consumption, particularly with proof-of-work (PoW) mechanisms like Bitcoin. The literature highlights the sustainability challenges associated with this energy consumption. Several strategies have been proposed to mitigate these impacts, such as optimizing cryptographic puzzles, implementing two-round mining processes, and integrating renewable energy sources. Alternative consensus mechanisms like Proof-of-Stake (PoS) and Proof-of-Authority (PoA) are also explored. This research project aims to evaluate the energy consumption profiles of existing blockchain systems and propose new, more efficient consensus algorithms. It also focuses on integrating renewable energy sources and optimizing smart contracts to reduce their resource consumption. A thorough security analysis will ensure that energy efficiency improvements do not compromise network security and decentralization. Using simulation tools, this research will quantify the improvements brought by new algorithms and strategies, contributing to the sustainability and broader adoption of blockchain technology in an environmentally conscious manner.
Development of the Compton-TDCR Method for Scintillator Metrology
The objectives of this PhD thesis lie upstream of the applied domain, specifically in the field of radionuclide metrology. The research aims to obtain essential information for a deeper understanding of scintillation mechanisms. This topic represents a new discipline within the national metrology laboratory, currently nonexistent in other laboratories, and focuses specifically on scintillator metrology. The work will be centered on instrumentation and data analysis, enabling a refined understanding of the underlying physical phenomena. The PhD will be co-supervised by Benoit Sabot (expert in radioactivity metrology) and Christophe Dujardin (expert in scintillation).
One of the primary experimental objectives of this PhD is the development and implementation of the new Compton-TDCR setup [7], designed for the absolute measurement of scintillation yield as a function of electron energy. This system will be designed using 3D printing technology and will integrate high-purity germanium (GeHP) detectors to enhance measurement precision. After characterizing these detectors in terms of energy resolution and efficiency, they will be integrated into the final experimental setup. The PhD candidate will be responsible for signal processing using a digital module generating List-Mode files. The data will then be analyzed using an existing Rust-based software with a Python interface, which is currently limited to four channels. Given that the new setup will incorporate up to three GeHP detectors in addition to three photomultiplier channels, the software must be adapted to ensure optimal processing of the acquired data. Following fine-tuning of the electronics and a series of experimental tests, the required software modifications will be implemented to enable full data exploitation from the platform.
Once this initial phase is completed and the platform is fully operational, the candidate will focus on investigating scintillation phenomena. The first studies will examine standard scintillating materials, such as organic (liquid or plastic) and inorganic scintillators. Subsequently, the research will extend to less explored materials, such as porous scintillators. This phase will involve close collaboration with the University of Lyon, particularly with the Institut Lumière Matière, where complementary measurements will be performed to refine the analysis of scintillation phenomena, complete the laboratory findings, and develop simulations that integrate various experimental approaches.
The ultimate goal of this setup is to establish a metrology methodology for scintillators, enabling access to the response curve of these materials as a function of the energy of electrons interacting within them, as well as their temporal properties. This work will pave the way for new ionizing radiation measurement techniques and will make a significant contribution to the scientific community in this field.
Alternatives to perfluorinated compounds for water-repellent and oil-repellent treatments of textiles used for NRBC personal body protection
Finding alternatives to fluorinated compounds (PFAS) involves very diverse application areas. Among them, the treatment of technical textiles to make them water- and oil-repellent is a major challenge for manufacturing protective clothing against both aqueous and oily contaminants. Our laboratory is developing such alternatives by covalently grafting molecules onto fibers selected from those already used for technical textiles. The thesis will focus on experimental work with two components. The first component will consist of improving and qualifying, at a semi-industrial level, the water- and oil-repellent properties already obtained and qualified according to current standards (water and oil droplet sliding, slow impregnation of oil droplets) using our nanometric chemical coatings. The second component will be dedicated to optimizing the weave structure, in conjunction with the chemical treatment, to determine the optimal weave based on the desired properties. The work will be carried out in close contact with a technical textile manufacturer and with ENSAIT in Roubaix.
Towards eco innovative, sustainable and reliable piezoelectric technology
Are you looking for a Phd position at the intersection of eco-innovation and high-tech? This subject is for you!
You will participate in efforts aimed at reducing the environmental footprint of piezoelectric (PZE) technology applied to micro actuators and sensors, while maintaining optimal levels of electrical performance and reliability. Currently PZE technology primarily relies on PZT material (Pb(Zr,Ti)O3) which contains lead, as well as electrodes made from materials such as Pt, Ru, and Au, along with doping elements like La, Mn and Nb to enhance piezoelectric properties and electrical performance. These materials not only come with a significant ecological cost but are also facing proven or imminent shortages. In the context of the necessary frugality associated with the energy transition, this PhD position aims to explore more environmentally friendly and sustainable microsystem technologies. The research will create a comparative analysis assessing the ecological footprint, electromechanical performance, and reliability of existing technologies (with lead) versus those under development (lead free). To achieve these objectives, you will employ Life Cycle Analyses (LCA), electromechanical measurements, and reliability tests (accelerated aging tests).
This interdisciplinary research will encompass fields such as eco design materials science, and microelectronic manufacturing processes You will benefit from the support of laboratories specializing in microsystems manufacturing and integration processes, as well as electrical characterization and reliability Collaboration with the “eco innovation” unit at CEA Leti will also enhance the resources available for this project.
Micro-needles functionalized with aptamers for the optical detection of cortisol
Compact, wearable medical devices, by offering autonomous and continuous monitoring of biomarkers, open the way to precise monitoring of pathologies outside of care centers and to a personalized therapeutic approach. The thesis project aims to develop wearable sensors based on microneedles (MNs) made of biomaterials for the minimally invasive detection of cortisol in the interstitial fluid (ISF) of the skin. Cortisol is one of the important biomarkers of physical and psychological stress, and is linked to the development of chronic diseases. ISF, a very rich source of biomarkers, offers an alternative to blood as a minimally invasive biofluid for cortisol quantification, and can be continuously analyzed by microneedle devices. Thus, swelling microneedles made of crosslinked biopolymer hydrogel have been developed at CEA-Leti over the last three years for ISF collection and analysis. The objective of the project will be to functionalize the hydrogel with a cortisol-sensitive aptamer molecular beacon, whose fluorescence will be activated in the specific presence of this metabolite, drawing on the expertise of the DPM NOVA team. Wearable optical sensors based on cortisol-sensitive MN patches will be designed, exploring two configurations: MN patches entirely made of hydrogel, and hybrid MN patches comprising an optical waveguide biopolymer and a cortisol-sensitive hydrogel coating. Different needle/waveguide shapes will be explored to optimize the fluorescence detection performance of the biosensors. The ability of the devices to puncture a skin model, sample artificial ISF, and detect the target will also be evaluated. The study will include biocompatibility tests, as well as a comparison with current methods for measuring serum cortisol by immunoassay.
Out-of-Distribution Detection with Vision Foundation Models and Post-hoc Methods
The thesis focuses on improving the reliability of deep learning models, particularly in detecting out-of-distribution (OoD) samples, which are data points that differ from the training data and can lead to incorrect predictions. This is especially important in critical fields like healthcare and autonomous vehicles, where errors can have serious consequences. The research leverages vision foundation models (VFMs) like CLIP and DINO, which have revolutionized computer vision by enabling learning from limited data. The proposed work aims to develop methods that maintain the robustness of these models during fine-tuning, ensuring they can still effectively detect OoD samples. Additionally, the thesis will explore solutions for handling changing data distributions over time, a common challenge in real-world applications. The expected results include new techniques for OoD detection and adaptive methods for dynamic environments, ultimately enhancing the safety and reliability of AI systems in practical scenarios.