Theoretical studies of orbital current and their conversion mechnism for leveraging spin-orbit torques based devices performances
The proposed PhD thesis aims at understanding and identifying the key parameters governing the conversion of orbital moments into spin currents, with the goal of enhancing the write efficiency of spin-orbit torque magnetic random-access memory (SOT-MRAM) devices. The work will employ a multiscale modeling approach comprising ab initio, tight-binding and atomistic calculations of the Orbital Hall Effect (OHE) and Orbital Rashba-Edelstein Effect (OREE). These phenomena exhibit larger magnitudes and diffusion lengths compared to their spin counterparts, Spin Hall Effect (SHE) and Rashba-Edelstein Effect (REE). Furthermore, they are present in a broader range of materials, including low-resistivity light metals. This opens very interesting opportunities for more efficient and conductive materials, potentially lifting the barriers limiting the technological deployment of SOT-MRAM.
This thesis will play a key role in a close collaboration between SPINTEC and LETI laboratories at CEA. The PhD student will conduct ab initio calculations at SPINTEC to unveil fundamental material characteristics to exploit the described orbitronic phenomena, and will construct multi-orbital Hamiltonians at LETI to calculate orbital and spin transport, in strong interaction/synergy with experimentalists working on SOT-MRAM development. The PhD will be co-supervised by M. Chshiev, K. Garello at Spintec and J. Li at LETI. This PhD project will be at the heart of collaborations with leading theoretical and experimental groups at national and international level.
Highly motivated candidates with a strong background in solid-state physics, condensed matter theory, and numerical simulations are encouraged to apply. The selected candidate will perform calculations using Spintec’s computational cluster, leveraging first-principles DFT-based packages and other simulation tools. Results will be rigorously analyzed, with opportunities for publication in international peer-reviewed journals.
Optical intradermal sensing via instrumented microneedles
Cortisol plays a central role in regulating the circadian cycle and in many essential physiological processes such as energy metabolism and immune response. Conventional monitoring of cortisol relies on single blood or saliva samples, which do not accurately reflect the temporal dynamics of its secretion. It is therefore necessary to develop innovative approaches that enable continuous, minimally invasive, and reliable measurement of cortisol concentration in patients.
The doctoral project aims to develop an original optical instrumentation system coupled with microneedles functionalized with fluorescent aptamers for continuous, minimally invasive intradermal monitoring of cortisol without the need for sampling. Within this framework, the PhD candidate will be responsible for designing and sizing the future optical microneedles intended for cortisol detection. They will set up the experimental systems required to characterize the optical microneedles fabricated within the department and test their performance in a representative environment. Finally, the PhD candidate will develop a comprehensive data processing and analysis methodology to identify the key parameters that establish a quantitative relationship between the collected signals and cortisol concentration. Altogether, this work will contribute to the development of an innovative measurement device based on cutting-edge optical emission and detection technologies available at CEA Leti, combining precision, sensitivity, compactness, and thus compatibility with in situ use.
On-line monitoring of bioproduction processes using 3D holographic imaging
The culture of adherent is a promising approach for various bioproduction applications, such as drug manufacturing and delivery, regenerative medicine, and tracking of cellular differentiation. However, the analysis of single cell morphology and behavior without affecting the substrate integrity remains a major challenge. Lens-free holographic imaging is emerging as a promising solution for real-time, non-invasive monitoring of cellular processes. This technique captures wide field of view images without requiring exogenous labeling or sample manipulation, thus preserving the integrity of the cellular environment.
This thesis proposes the development of a 3D lens-free imaging system to monitor adherents cells in near real-time. The microscope will be coupled with advanced algorithms for data reconstruction and analysis and tested on different cell models. The use of deep learning techniques will allow for real-time segmentation and analysis of single cells, facilitating the tracking of cellular dynamics. This innovative project paves the way to a non-invasive monitoring of 3D multicellular samples, with potential applications on organ-on-chip and more complex organoids systems.
Artificial Intelligence for the Modeling and Topographic Analysis of Electronic Chips
The inspection of wafer surfaces is critical in microelectronics to detect defects affecting chip quality. Traditional methods, based on physical models, are limited in accuracy and computational efficiency. This thesis proposes using artificial intelligence (AI) to characterize and model wafer topography, leveraging optical interferometry techniques and advanced AI models.
The goal is to develop AI algorithms capable of predicting topographical defects (erosion, dishing) with high precision, using architectures such as convolutional neural networks (CNN), generative models, or hybrid approaches. The work will include optimizing models for fast inference and robust generalization while reducing manufacturing costs.
This project aligns with efforts to improve microfabrication processes, with potential applications in the semiconductor industry. The expected results will contribute to a better understanding of surface defects and the optimization of production processes.
Thermodynamic and experimental approach of the reactivity in multi-constituted Silicon-Metal-Carbon systems for ceramic brazing
The development of ceramic-based material assemblies plays a fundamental role in technological innovation in many engineering fields. The choice of materials and joining process must ensure a functional, reliable and durable assembly, whose properties comply with the specifications of the application.
The PhD thesis is part of the development of brazing alloys optimized for the joining of ceramics (primarily silicon carbide) considered for various applications in harsh environments, particularly in the field of energy. Indeed, the design of these materials requires a good knowledge of the reactivity at the liquid alloy / ceramic interface. In this context, the thesis will contribute to the development of a thermodynamic and experimental approach to predict and understand the reactivity in multi-constituted Si-Metal-Carbon systems. This work includes a study of the wetting and interfacial reactivity of selected alloys (wetting and brazing experiments, fine characterization of the interfaces by different techniques such as FEG-SEM, X-ray diffraction, TEM, XPS) with the support of thermodynamic modelling using the CALPHAD method. This highly experimental work will be carried out in a dynamic and collaborative environment.
Adjoint sensitivity method applied to industrial modeling of nuclear reactor cores
The objective of this thesis is to lay the foundations for applying the adjoint sensitivity method to industrial modeling of solid fuel nuclear reactor cores. The main topic will be the consideration of the coupling between neutronics, thermohydraulics, heat diffusion in fuel rods, and evolution.
Analysis and design of dispersion-engineered impedance surfaces
Dispersion engineering (DE) refers to the control of how electromagnetic waves propagate in a structure by shaping the relationship between frequency and phase velocity. Using artificially engineered materials and surfaces, this relationship can be tailored to achieve non-conventional propagation behaviors, enabling precise control of dispersive effects in the system. In antenna design, dispersion engineering can enhance several key aspects of radiation performance, including gain bandwidth, beam-scanning accuracy, and in general the reduction of distortions that arise when the operating frequency changes. It can also enable additional functionalities, such as multiband operation or multifocal behavior in lens- and reflector-based antennas.
This thesis aims to investigate the underlying physics governing the control of phase and group velocities in two-dimensional artificial surfaces with frequency-dependent effective impedance properties. A particular emphasis will be placed on spatially fed architectures, such as transmitarrays and reflectarrays, where dispersion plays a crucial role. The objective is to derive analytical formulations within simultaneously control of both group and phase delay, develop general models, and assess the fundamental limitations of such systems in radiation performance. This work is especially relevant for high-gain antenna architectures, where the state of the art remains limited. Current dispersion-engineered designs are mostly narrowband, and no compact high-gain solution (> 35 dBi) has yet overcome dispersion-induced degradations, which lead to gain drop and beam squint.
The student will develop theoretical and numerical tools, investigate new concepts of periodic unit cells for the impedance surfaces, and design advanced antenna architectures exploiting principles such as true-time delay, shared-aperture multiband operation, or near-field focsuing with minimized chromatic aberrations. The project will also explore alternative fabrication technologies to surpass the constraints of standard PCB processes and unlock new dispersion capabilities.
Plasma real time control by calorimetry
Inside thermonuclear fusion devices, plasma facing components are subject to intense heat fluxes. The WEST tokamak has water cooled plasma facing components to limit their heating. Calorimetric measurement on these components allows for the measurement of the power received by each component. This makes it possible to control the plasma position or the additional plasma heating in function of the power distribution.
During this PhD, a simulation of plasma control using calorimetry will be performed, simulating the heat fluxes received by the components as a function of the plasma position and the associated calorimetric response. In-situ calorimetric measurements will be carried out on the components at the top and bottom of the machine during dedicated plasma experiments to refine the simulations and the control of the WEST plasma position based on calorimetric measurements will finally be implemented and validated during dedicated experiments, for plasma-facing components protection and plasma physics purposes.
Investigation and Modeling of Ferroelectric and Antiferroelectric Domain Dynamics in HfO2-Based Capacitors
The proposed PhD work lies within the exploration of new supercapacitor and hybrid energy storage technologies, aiming to combine miniaturization, high power density, and CMOS process compatibility. The hosting laboratory (LTEI/DCOS/LCRE) has recognized expertise in thin-film integration and dielectric material engineering, offering unique opportunities to investigate ferroelectric (FE) and antiferroelectric (AFE) behaviors in doped hafnium oxide (HfO2).
The thesis will focus on the experimental investigation and physical modeling of thin-film HfO2-based capacitors, intentionally doped to exhibit ferroelectric or antiferroelectric properties depending on the composition and deposition conditions (for instance, through ZrO2 or SiO2 doping). Such materials are particularly attractive for realizing devices that combine non-volatile memory and energy storage functions on a single CMOS-compatible platform, enabling ultra-low-power autonomous systems such as edge computing architectures, environmental sensors, and smart connected objects.
The research will involve the fabrication and characterization of metal–insulator–metal (MIM) capacitors based on doped HfO2 integrated on silicon substrates. Systematic electrical measurements—including current–voltage (I–V) and polarization–electric field (P–E) characterizations—will be carried out under various frequencies, amplitudes, and cycling conditions to investigate the relaxation mechanisms of FE and AFE domains. Analysis of minor hysteresis loops will provide access to the distribution of activation energies and enable the modeling of domain relaxation dynamics. A physical model will be developed or refined to describe FE/AFE transitions under cyclic electrical excitation, incorporating effects such as charge trapping, mechanical stress, and domain nucleation kinetics.
The overall objective is to optimize the recoverable energy density and the energy conversion efficiency of these capacitors, while establishing design guidelines for compact, efficient, and silicon-integrable energy storage devices. The insights gained from this work will contribute to a deeper understanding of the dynamic mechanisms governing FE/AFE behavior in doped HfO2, with potential impact on ferroelectric memories, energy-harvesting devices, and low-power neuromorphic architectures.
Methods for the Rapid Detection of Gravitational Events from LISA Data
The thesis focuses on the development of rapid analysis methods for the detection and characterization of gravitational waves, particularly in the context of the upcoming LISA (Laser Interferometer Space Antenna) space mission planned by ESA around 2035. Data analysis involves several stages, one of the first being the rapid analysis “pipeline,” whose role is to detect new events and to characterize them. The final aspect concerns the rapid estimation of the sky position of the gravitational wave source and their characteristic time, such as the coalescence time in the case of black hole mergers. These analysis tools constitute the low-latency analysis pipeline.
Beyond its value for LISA, this pipeline also plays a crucial role in the rapid follow-up of events detected by electromagnetic observations (ground or space-based observatories, from radio waves to gamma rays). While fast analysis methods have been developed for ground-based interferometers, the case of space-borne interferometers such as LISA remains an area to be explored. Thus, a tailored data processing method will have to consider the packet-based data transmission mode, requiring event detection from incomplete data. From data affected by artifacts such as glitches, these methods must enable the detection, discrimination, and analysis of various sources.
In this thesis, we propose to develop a robust and effective method for the early detection of massive black hole binaries (MBHBs). This method should accommodate the data flow expected for LISA, process potential artifacts (e.g., non-stationary noise and glitches), and allow the generation of alerts, including a detection confidence index and a first estimate of the source parameters (coalescence time, sky position, and binary mass); such a rapid initial estimate is essential for optimally initializing a more accurate and computationally expensive parameter estimation.