Structural snapshots of a substrate within the active site of a mitogen-activated protein kinase
Mitogen-activated protein kinases (MAPKs) are key signaling enzymes that regulate cellular stress responses through the phosphorylation of specific protein substrates. Dysregulation of MAPK signaling contributes to numerous diseases, including cancer and neurodegenerative disorders. Although MAPK activation and catalytic mechanisms are well characterized, the structural basis of substrate specificity remains unknown. This project aims to address this gap by capturing atomic-level structural snapshots of substrates bound within the active site of the c-Jun N-terminal kinase 1 (JNK1). To achieve this, we will employ X-ray crystallography together with innovative nuclear magnetic resonance (NMR) methods that integrate selective methyl isotope labeling and photoactivatable catalysis. By elucidating the structural details of how substrates are recognized by the active site of JNK1, our work will open new avenues for the development of substrate-competitive inhibitors of MAPKs with enhanced selectivity and therapeutic potential.
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.
III-V semiconductor nanoplatelets
Colloidal semiconductor nanoplatelets (NPLs) are a class of two-dimensional nanostructures that have electronic and optical properties distinct from those of spherical quantum dots (QDs). They exhibit strong quantum confinement in a single dimension, their thickness, which can be controlled on the monolayer level using solution chemistry. As a result, NPLs emit light with an extremely narrow spectral width and at the same time, they have a very high absorption coefficients. These properties make them ideal candidates for various applications (e.g., light-emitting diodes for low-power-consumption displays, photocatalysis, single-photon emitters).
At present, only the synthesis of metal chalcogenide NPLs has been mastered. These materials either contain toxic elements (CdSe, HgTe, etc.) or have a large bandgap (ZnS, ZnSe). For these reasons, the development of synthesis methods for III-V semiconductor NPLs, such as InP, InAs and InSb is currently a major challenge. In this thesis, we will develop new synthetic approaches for the growth of InP NPLs, exploring different avenues and using in situ characterizations as well as machine learning assisted design of experiments. Numerical simulations will be used to determine the reactivity of precursors and to model the mechanisms inducing anisotropic growth.
Impact of magnetohydrodynamic on access and dynamics of X-point radiator regimes (XPR)
ITER and future fusion powerplants will need to operate without degrading too much the plasma facing components (PFC) in the divertor, the peripheral element with is dedicated to heat and particle exhaust in tokamaks. In this context, two key factors must be considered: heat fluxes must stay below engineering limits both in stationary conditions and during violent transient events. An operational regime recently developed can satisfy those two constraints: the X-point Radiator (XPR). Experiments on many tokamaks, in particular WEST which has the record plasma duration in this regime (> 40 seconds), have shown that it allowed to drastically reduce heat fluxes on PFCs by converting most of the plasma energy into photons and neutral particles, and that it also was able to mitigate – or even suppress – deleterious magnetohydrodynamic (MHD) edge instabilities known as ELMs (edge localised modes). The mechanisms governing these mitigation and suppression are still poorly understood. Additionally, the XPR itself can become unstable and trigger a disruption, i.e., a sudden loss of plasma confinement cause by global MHD instabilities.
The objectives of this PhD are: (i) understand the physics at play during the interaction XPR-ELMs, and (ii) optimise the access and stability of the XPR regime. To do so, the student will use the 3D non linear MHD code JOREK, the European reference code in the field. The goal is to define the operational limits of a stable XPR with small or no ELMs, and identify the main actuators (quantity and species of injected impurities, plasma geometry).
A participation to experimental campaigns of the WEST tokamak (operated by IRFM at CEA Cadarache) – and of the MAST-U tokamak operated by UKAEA – is also envisaged to confront numerical results and predictions to experimental measurements.
Point Spread Function Modelling for Space Telescopes with a Differentiable Optical Model
Context
Weak gravitational lensing [1] is a powerful probe of the Large Scale Structure of our Universe. Cosmologists use weak lensing to study the nature of dark matter and its spatial distribution. Weak lensing missions require highly accurate shape measurements of galaxy images. The instrumental response of the telescope, called the point spread function (PSF), produces a deformation of the observed images. This deformation can be mistaken for the effects of weak lensing in the galaxy images, thus being one of the primary sources of systematic error when doing weak lensing science. Therefore, estimating a reliable and accurate PSF model is crucial for the success of any weak lensing mission [2]. The PSF field can be interpreted as a convolutional kernel that affects each of our observations of interest, which varies spatially, spectrally, and temporally. The PSF model needs to be able to cope with each of these variations. We use specific stars considered point sources in the field of view to constrain our PSF model. These stars, which are unresolved objects, provide us with degraded samples of the PSF field. The observations go through different degradations depending on the properties of the telescope. These degradations include undersampling, integration over the instrument passband, and additive noise. We finally build the PSF model using these degraded observations and then use the model to infer the PSF at the position of galaxies. This procedure constitutes the ill-posed inverse problem of PSF modelling. See [3] for a recent review on PSF modelling.
The recently launched Euclid survey represents one of the most complex challenges for PSF modelling. Because of the very broad passband of Euclid’s visible imager (VIS) ranging from 550nm to 900nm, PSF models need to capture not only the PSF field spatial variations but also its chromatic variations. Each star observation is integrated with the object’s spectral energy distribution (SED) over the whole VIS passband. As the observations are undersampled, a super-resolution step is also required. A recent model coined WaveDiff [4] was proposed to tackle the PSF modelling problem for Euclid and is based on a differentiable optical model. WaveDiff achieved state-of-the-art performance and is currently being tested with recent observations from the Euclid survey.
The James Webb Space Telescope (JWST) was recently launched and is producing outstanding observations. The COSMOS-Web collaboration [5] is a wide-field JWST treasury program that maps a contiguous 0.6 deg2 field. The COSMOS-Web observations are available and provide a unique opportunity to test and develop a precise PSF model for JWST. In this context, several science cases, on top of weak gravitational lensing studies, can vastly profit from a precise PSF model. For example, strong gravitational lensing [6], where the PSF plays a crucial role in reconstruction, and exoplanet imaging [7], where the PSF speckles can mimic the appearance of exoplanets, therefore subtracting an accurate and precise PSF model is essential to improve the imaging and detection of exoplanets.
PhD project
The candidate will aim to develop more accurate and performant PSF models for space-based telescopes exploiting a differentiable optical framework and focus the effort on Euclid and JWST.
The WaveDiff model is based on the wavefront space and does not consider pixel-based or detector-level effects. These pixel errors cannot be modelled accurately in the wavefront as they naturally arise directly on the detectors and are unrelated to the telescope’s optic aberrations. Therefore, as a first direction, we will extend the PSF modelling approach, considering the detector-level effect by combining a parametric and data-driven (learned) approach. We will exploit the automatic differentiation capabilities of machine learning frameworks (e.g. TensorFlow, Pytorch, JAX) of the WaveDiff PSF model to accomplish the objective.
As a second direction, we will consider the joint estimation of the PSF field and the stellar Spectral Energy Densities (SEDs) by exploiting repeated exposures or dithers. The goal is to improve and calibrate the original SED estimation by exploiting the PSF modelling information. We will rely on our PSF model, and repeated observations of the same object will change the star image (as it is imaged on different focal plane positions) but will share the same SEDs.
Another direction will be to extend WaveDiff for more general astronomical observatories like JWST with smaller fields of view. We will need to constrain the PSF model with observations from several bands to build a unique PSF model constrained by more information. The objective is to develop the next PSF model for JWST that is available for widespread use, which we will validate with the available real data from the COSMOS-Web JWST program.
The following direction will be to extend the performance of WaveDiff by including a continuous field in the form of an implicit neural representations [8], or neural fields (NeRF) [9], to address the spatial variations of the PSF in the wavefront space with a more powerful and flexible model.
Finally, throughout the PhD, the candidate will collaborate on Euclid’s data-driven PSF modelling effort, which consists of applying WaveDiff to real Euclid data, and the COSMOS-Web collaboration to exploit JWST observations.
References
[1] R. Mandelbaum. “Weak Lensing for Precision Cosmology”. In: Annual Review of Astronomy and Astro- physics 56 (2018), pp. 393–433. doi: 10.1146/annurev-astro-081817-051928. arXiv: 1710.03235.
[2] T. I. Liaudat et al. “Multi-CCD modelling of the point spread function”. In: A&A 646 (2021), A27. doi:10.1051/0004-6361/202039584.
[3] T. I. Liaudat, J.-L. Starck, and M. Kilbinger. “Point spread function modelling for astronomical telescopes: a review focused on weak gravitational lensing studies”. In: Frontiers in Astronomy and Space Sciences 10 (2023). doi: 10.3389/fspas.2023.1158213.
[4] T. I. Liaudat, J.-L. Starck, M. Kilbinger, and P.-A. Frugier. “Rethinking data-driven point spread function modeling with a differentiable optical model”. In: Inverse Problems 39.3 (Feb. 2023), p. 035008. doi:10.1088/1361-6420/acb664.
[5] C. M. Casey et al. “COSMOS-Web: An Overview of the JWST Cosmic Origins Survey”. In: The Astrophysical Journal 954.1 (Aug. 2023), p. 31. doi: 10.3847/1538-4357/acc2bc.
[6] A. Acebron et al. “The Next Step in Galaxy Cluster Strong Lensing: Modeling the Surface Brightness of Multiply Imaged Sources”. In: ApJ 976.1, 110 (Nov. 2024), p. 110. doi: 10.3847/1538-4357/ad8343. arXiv: 2410.01883 [astro-ph.GA].
[7] B. Y. Feng et al. “Exoplanet Imaging via Differentiable Rendering”. In: IEEE Transactions on Computational Imaging 11 (2025), pp. 36–51. doi: 10.1109/TCI.2025.3525971.
[8] Y. Xie et al. “Neural Fields in Visual Computing and Beyond”. In: arXiv e-prints, arXiv:2111.11426 (Nov.2021), arXiv:2111.11426. doi: 10.48550/arXiv.2111.11426. arXiv: 2111.11426 [cs.CV].
[9] B. Mildenhall et al. “NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis”. In: arXiv e-prints, arXiv:2003.08934 (Mar. 2020), arXiv:2003.08934. doi: 10.48550/arXiv.2003.08934. arXiv:2003.08934 [cs.CV].
Study of impurity transport in negative and positive triangularity plasmas
Nuclear fusion in a tokamak is a promising source of energy. However, a question arises: which plasma configuration is most likely to produce net energy? In order to contribute to answering this, during this PhD, we will study the impact of magnetic geometry (comparison between positive and negative triangularity) on the collisional and turbulent transport of tungsten (W). The performance of a tokamak strongly depends on the energy confinement it can achieve. The latter degrades significantly due to turbulent transport and radiation (primarily from W). On ITER, the tolerated amount of W in the core of the plasma is about 0.3 micrograms. Experiments have shown that the plasma geometry with negative triangularity (NT) is beneficial for confinement as it significantly reduces turbulent transport. With this geometry, it is possible to reach confinement levels similar to those of the ITER configuration (H-mode in positive triangularity), without the need for a minimum power threshold and without the associated plasma edge relaxations. However, questions remain: what level of W transport is found in NT compared to a positive geometry? What level of radiation can be predicted in future NT reactors? To contribute to answering these questions, during this PhD, we will evaluate the role of triangularity on impurity transport in different scenarios in WEST. The first phase of the work is experimental. Subsequently, the modeling of impurity transport will be carried out using collisional and turbulent models. Collaboration is planned with international plasma experts in NT configurations, with UCSD (United States) and EPFL (Switzerland).
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).
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.
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.
Development of monoclonal antibodies for the diagnostic and the treatement of hypervirulent-Klebsiella pneumoniae
For several years, we have observed the emergence of hypervirulent (hvKp) strains of Klebsiella pneumoniae that have become highly resistant to antibiotics. In a context of dwindling antibiotic options, monoclonal antibodies (Abs) directed against well-conserved capsular antigens of these hvKp strains appear as a promising therapeutic alternative.
This PhD project is structured around three complementary objectives:
1. To describe the circulation of hvKp clones through comparative genomic analysis of strains collected via the French National Reference Center for Antibiotic Resistance and through an international collaboration.
2. To produce and characterize monoclonal Abs directed against the HvKp capsule.
3. To develop a rapid detection tool based on MALDI-TOF profile analysis coupled with machine learning algorithms.