Etch and integration of phase change materials for reconfigurable photonic

Chalcogenide glasses are materials of interest for many applications: in phase-change memories, for example optical storage (CD-RW, DVD-RAM, Blu-ray Disks) or more recently Storage Class Memory, as a selector in 3D architecture resistive memories (OTS selector) or as an active medium for non-linear optics and reconfigurable photonics. In the latter case, the production of metasurfaces with controllable optical refractive indices and the development of photonic actuators is a subject of renewed interest, given the unique optical properties of these materials.
In this field, CEA-LETI is one of the major international players in the development of thin films of chalcogenide glasses and phase-change materials, as well as in the characterization and understanding of their unusual physical properties. Today, although these materials are well mastered at industrial level for memory applications, it is nevertheless necessary to work on integrating these innovative, high-performance materials into small-scale structures while preserving their unique physical properties. Initial integration studies carried out during a previous thesis showed that the etching and stripping process steps were far from being optimized, even though they are critical if the properties of the material are not to be degraded during the production of photonic structures. Although essential for process control, the etching mechanisms of chalcogenide glasses are relatively poorly described in the literature, with the exception of Ge2Sb2Te5 used in phase-change memories.
This theme is therefore innovative and has real added value. The aim of the thesis is therefore to study and understand the etching mechanisms of GeSbSeTe-based chalcogenide glasses in order to control the profile and size of the transferred structures. The work to be carried out is highly experimental and will take place mainly in the LETI's 300 mm clean room. The candidate will have access to state-of-the-art chalcogenide materials thin films, an industrially designed plasma etching reactor and a wide range of characterization facilities. This thesis will be carried out in collaboration with the LETI advanced materials deposition service and the optoelectronic devices applications department (DOPT).

Contribution of metal-semiconductor interfaces to the operation of the latest generation of infrared photodiodes

This thesis concerns the field of cooled infrared detectors used for astrophysical applications. In this field, the DPFT/SMTP (Infrared Laboratory) of CEA-LETI-MINATEC works closely with Lynred, a world leader in the production of high-performance infrared focal planes. In this context, the infrared laboratory is developing new generations of infrared detectors to meet the needs of future products.
One of the current development axes concerns the quality of the p-type semiconductor metal interface. These developments are driven by the increase in the operating temperature of the detectors, as well as by the very strong performance requirements for space applications.
The challenge of this thesis is to contribute to a better understanding of the chemical species present at the interface of interest as a function of different surface treatment types and to link them to the electrical properties of the contact made.
The candidate will join the infrared laboratory, which includes the entire detector production process. He/she will produce these samples using the technological means available in the LETI clean room, in collaboration with experts in the field. He/she will also have access to the necessary characterization tools (SIMS, XPS, AFM…) available on the nano-characterization platform (PFNC) or in the CEA clean room. Finally, he/she will be involved in the electro-optical characterization of the material, in collaboration with the Cooled Infrared Imaging Laboratory (LIR), which specializes in fine material characterization.

Anisotropies and deformations induced by doping in the latest generation of infrared photodiodes

This thesis concerns the field of HgCdTe infrared detectors for astrophysical applications, for which the Infrared Laboratory of CEA -Leti is one of the world leaders.
The candidate will join the infrared laboratory, which includes the entire detector production process. As a participant in all discussions on the development of CdHgTe samples, he will produce them using the technological means of elaboration available in the Leti clean room, in collaboration with experts in the field.
These samples will then be characterized using our access to synchrotron radiation from ESRF as well as the nano-characterization platform of CEA-Grenoble equipped with a set of state-of-the-art characterization techniques. By studying the changes induced by variations in the sample preparation process using Laue micro-diffraction and SEM-EDX, simultaneous 2D mapping at a submicron scale of local stress and chemical composition will be accessed.
The challenge of this thesis will be to analyse the correlations between chemical composition and local stress, in relation to the specificities of the preparation process. The objective will be to study the mechanisms behind anisotropic behaviour in the structures of interest.

Advancing image sensor security: using deep learning for simultaneous robust and fragile watermarking

This PhD project aims at advancing the field of image sensor security through a comprehensive exploration of recent deep learning techniques applied to both robust and fragile invisible watermarking. In the specific context of embedded image rendering pipelines, this study aims to address the dual challenges of ensuring resistance against intentional attacks to break the mark (robust watermarking) while maintaining a high sensitivity to alterations (fragile watermarking). The goal of this multifaceted design approach is not only to enhance the security of imager data but additionally opens avenues for applications in authentication, tamper and forgery detection, combined with data integrity checking. The research will delve into fields of research from image sensor rendering pipeline design using attention-augmented deep learning models to the intricacies of embedding multiple watermarks simultaneously, addressing the requirement for both robust and fragile characteristics.
This research is therefore an exciting opportunity for PhD candidates showing interest in the intersection of deep learning, image processing, and security. It provides not only a rich academic landscape for impactful scientific contributions but also holds potential for concrete results for upcoming technological transfers. In practice, the work will consists in finding novel algorithmic solutions to improve watermarking performance, designed to deal with most advanced Deep Learning based attacks, while maintaining a high image quality rendering.