Control of trapped electron mode turbulence with an electron cyclotron resonant source
The performance of a tokamak-type fusion power plant in term of energy gain will be limited by turbulent transport. The instability of trapped electron modes is one of the main instabilities causing turbulence in tokamaks. Furthermore, electron cyclotron resonance heating (ECRH) is the generic heating system in current and future tokamaks. Both physical processes are based on resonant interactions with electrons, in space and velocity. Since heating has the effect of depopulating the resonant interaction zone of its electrons, superimposing its resonance on that of the instability can theoretically lead to a stabilisation of the trapped electron modes.
The objective of the thesis is twofold: (i) to construct scenarios where this mechanism exists and validate it using linear simulations, then (ii) to characterise its effect and quantify its effectiveness in non-linear regimes where linear effects compete with the self-organisation of turbulence, with collisional processes and with the dynamics of average profiles. Potentially, this entirely new control technique could improve the performance of tokamaks at no additional cost. The PhD thesis will require a detailed theoretical understanding of the two resonant processes and their various control parameters. It will be based on the use of the high performance computing gyrokinetic code GYSELA dedicated to the study of transport and turbulence in tokamak plasmas, which has recently been enhanced with an ECRH heating module. An experimental component is also planned on the WEST and/or TCV tokamaks to validate the identified most promising turbulence control scenario(s).
Adaptation and degradation of PFAS by the bacterium Pseudomonas putida
Per- and polyfluoroalkyl substances (PFASs) are a class of very diverse chemicals found in products of daily use, that are highly persistent and encountered everywhere in the environment. They accumulate/biomagnify within the natural food chain and show a relatively high toxicity including the alternative products developed after the ban of the legacy compounds. Therefore, the world is facing a situation of great concern all the more as the retreatment of contaminated soils, sediments and water is difficult and costly. One of the main challenges is because various PFASs have quite different physicochemical properties but are often encountered in mixture making it difficult to find a technology efficient to remove all of them. We propose to pave the way towards another approach for PFASs elimination, bioremediation that is known to be a good alternative to chemical or physical methods for removing toxics (self-sustainability, cheaper, working in milder conditions, and often with dissolved and sorbed contaminants). A few bacteria have been described to be able to partially modify/degrade some PFASs. However, except the aspect of PFAS transformation, no data are available concerning their adaptation to PFAS exposure. A few projects are focusing on finding enzymes implicated in the degradation per se but if we want to use bacterial cultures and not enzymes, many other parameters need to be taken into account to set up a performant strain and hence a performant process. Therefore, we propose to analyze in depth the response to several PFASs of the PFAS degrading strain Pseudomonas putida ATCC 17514 in term of degradation, adaptation to a potential toxicity and metabolism adjustment. The analyses will mainly rely on a proteomic approach that is a very powerful technique to analyze global responses without a priori, and has never been done to characterize PFASs toxicity or fluorinated compounds metabolism in bacteria. The ultimate goal after this bootstrap project will be to engineer or select a robust and efficient strain capable of biodegrading PFASs.
Acellular Biotherapy with Optimized Immunomodulatory Properties for the Prevention of Organ Injury in Traumatic Contexts
Severe trauma causes more than 5.8 million deaths worldwide each year, often associated with massive hemorrhages and multiple organ failure (approximately 33% of cases). Rhabdomyolysis, common in these patients, results from the destruction of muscle cells and leads to the release of their contents into the bloodstream. This complication promotes acute kidney injury and liver dysfunction. Currently, no specific treatment exists; management remains primarily symptomatic. Mesenchymal stromal cells (MSCs) are widely used for their immunomodulatory and regenerative properties. Preclinical studies have shown that IL-1ß-preconditioned MSCs can prevent kidney and liver damage and reduce vascular permeability after hemorrhagic shock. Their efficacy relies on the secretion of soluble factors and extracellular vesicles, known as acellular products. A large-scale, clinical-grade production method for these products, based on tangential flow filtration, has been developed. These products exhibit experimentally demonstrated immunomodulatory activity and hepatoprotective effects. Ready to use and easy to store, they represent a promising alternative to cell therapies in emergency settings. The objective of this thesis is to optimize the immunomodulatory and anti-inflammatory properties of these cell-free products by promoting their expression of two key immune tolerance molecules, PD-L1 and HLA-G. We will evaluate the interactions between these optimized products and various immune cells in vitro, and then in vivo in a traumatic hemorrhagic shock model (rat model).
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.
Influence of Cytomegalovirus on Tissue-Specific Immune Responses in Non-Human Primate
Most studies in anti-infectious immunity focus on characterizing pathogen-specific immune responses and identifying strategies to optimize them. It is now essential to consider interindividual variability related to age, sex, metabolic status, and infectious history, which strongly influence these responses.
IDMIT’s expertise in preclinical modeling of viral infections provides an ideal framework to address these questions. Cytomegalovirus (CMV) infection represents a relevant model due to its high prevalence, its age-dependent effects, and its association with immune aging. Although epidemiological data suggest that CMV seroprevalence impacts responses to other infections and to vaccination, the underlying mechanisms remain poorly understood. We hypothesize heterogeneous effects related to the diversity of host–virus interactions across sites of viral persistence.
This project aims to characterize CMV-specific immune responses in blood and tissues of young and aged non-human primates, and in the context of chronic SIV infection. The objectives are (i) to assess age-related differences in viral dissemination and immune responses, (ii) to evaluate the predictive value of blood markers relative to tissue parameters, and (iii) to study the reciprocal modulation of CMV and SIV responses during co-infection.
These studies will contribute to the development of vaccination strategies targeting the deleterious effects of CMV and the tissue-specific modulation of immune responses.
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.
Real-Time control of MHD instabilities during WEST long pulses
In magnetically confined plasmas, low-frequency (typ. 1-10 kHz) large-scale magnetohydrodynamic (MHD) instabilities represent a risk for performance and plasma stability. During long pulses in the WEST tokamak, deleterious MHD modes appear frequently inducing a drop of central temperature and a higher plasma resistivity that result in lower performances and shorter discharge duration. The real-time detection of such instabilities and the application of mitigation strategies is therefore of great importance for plasma control in WEST but also for future devices like ITER.
These MHD instabilities induce coherent temperature/density perturbations. Instruments like Electron Cyclotron Emission (ECE) radiometer or reflectometrer provide localized, high time resolution of temperature or density fluctuations. However, MHD analysis is currently performed offline, after the discharge. Real-time capability is crucial for control applications. The modes must first be identified before applying a mitigation strategy based on the knowledge of the MHD stability criteria. MHD stability is strongly affected by local heating and current drive, for which Electron Cyclotron Resonance Heating and Current Drive systems (ECRH/ECCD) are especially well suited.
The objective of this PhD is to develop a control strategy for WEST long pulse operation. The first step is the real-time detection of low frequency MHD instabilities using first ECE radiometer, then adding instruments like ECE-imaging or reflectometry to enhance reliability and accuracy. Integrated plasma modelling will then be performed to explore MHD mitigation strategies. ECCD is an obvious actuator, but other tools such as a temporary change of the plasma parameters (current, density or temperature) will also be evaluated. The mitigation strategy will be integrated in WEST Plasma Control System. Initial strategy will rely on simple control loop, then Neural Network or deep-leaning algorithms will be tested.
Active matter: self-organization of mitotic spindles
The mitotic spindle is an essential cytoskeletal structure that enables chromosome separation during cell division. This project seeks to identify the physical principles that control spindle assembly by using a simplified biomimetic system composed solely of microtubules and molecular motors. We will use motors of opposite polarities combined with dynamic microtubules to understand how these components organize through active phase separation. Indeed, preliminary experiments have demonstrated that such reconstituted systems can spontaneously form bipolar structures resembling mitotic spindles. We now propose to encapsulate these molecular components in compartments of controlled geometry to reconstruct a minimal bipolar structure capable of elongating, retracting, and separating its organizing poles. This multidisciplinary approach will combine biochemical and physicochemical techniques, advanced microscopy, and quantitative analysis of the spatial and temporal evolution of the system. The experimental work will be closely coupled with theoretical modeling in collaboration with Prof. Jean-François Joanny (Collège de France) to develop a physical model of active phase separation that will provide better understanding of self-organization mechanisms at the subcellular scale in living organisms.
Beam dynamics for a multi-stage laser-plasma accelerator
Laser–plasma wakefield accelerators (LWFAs) can provide accelerating gradients exceeding 100 GV/m, providing a pathway to reduce the size and cost of future high-energy accelerators for applications in synchrotron radiation, free-electron lasers, and emerging medical and industrial uses.
Scaling this technology to higher beam energies and charges requires both technological maturity and innovative acceleration schemes. Multi-stage configurations — connecting several plasma acceleration stages — offer key advantages: increasing beam energy beyond single-cell limits and enhancing total charge and/or repetition rate. These systems aim to overcome single-stage limitations while maintaining or improving beam quality at higher energies.
Designing an accelerator delivering stable, reproducible, high-quality beams requires comprehensive understanding of plasma acceleration physics and beam transport between successive stages.
Building on expertise at CEA Paris–Saclay's DACM, this PhD will focus on physical and numerical studies to propose a fully integrated multi-stage LWFA design, with particular attention to optimizing all components — plasma accelerating section and transport lines — to preserve beam quality in terms of transverse size, divergence, emittance, and energy spread.
Large scale simulation and machine learning in nucleon structure
The PhD proposal investigates the nucleon’s three-dimensional structure using Generalized Parton Distributions (GPDs). GPDs give access to the spatial distribution of quarks and gluons, the energy-momentum tensor, and thus information on spin, internal pressure, and mass. Two main challenges arise: scarce exclusive experimental data and the high cost of precise lattice-QCD simulated observables. The project comprises two parts: (I) generate new lattice-QCD simulations of GPD moments, improve algorithms, and perform continuum extrapolations; (II) create machine-learning tools to tackle the ill-posed inverse problem and conduct global fits that combine experimental and simulated data. The work will be carried out at the European Joint Virtual Lab AIDAS shared between Julich Forschungszentrum (Germany) and CEA (France), with equal time spent in each country. Required skills include quantum field theory, object-oriented programming (C++, Python), and high-performance computing. The ultimate goal is the first reliable extraction of the nucleon’s 3-D structure, informing future facilities such as the EIC and EicC.