Toughening random lattice metamaterials with structure heterogeneities
To reduce the environmental and/or the energetic impact of vehicles, a favored method is to decrease the mass of prime materials used to build them, that being done without hindering their mechanical performances. In this field, the use of mechanical metamaterials has been a major breakthrough. These metamaterials, generally created using additive manufacturing techniques, have a microscopic truss structure. They are porous by design, and thus very lightweight, and the distribution of their microscopic beams or tubes (i.e. their architecture) can be chosen to make them as stiff as possible, making them choice candidates for high technology applications where the rigidity-density ratio is paramount, such as aerospatial research (https://en.wikipedia.org/wiki/Metallic_microlattice).
For the most part however, metamaterials that have been designed up to now present periodical architectures. As a consequence, their mechanical behavior is inherently anisotropic, which makes them difficult to model using material mechanics conventional approaches, and strongly limits their usage in various possible fields of applications. In recent works, we have developped a new class of microlattice metamaterials with a random spatial distribution of beams, generated with a combination of random close packing and Delaunay triangulation algorithm then 3D-manufactured. These metamaterials show an isotropic mechanical behavior, and their stiffness-density ratio reaches the theoretical limit for porous materials. They are neverheless still fragile and subject to fracture and yielding.
The aim of this PhD project is to toughen these metamaterials based on techniques and mechanisms from polymer and soft matter physics. Our hypothesis is that including in a controlled statistical way structure heterogeneities, at the node level by modulating the connectivity or at the beam level by changing their section or shape, can allow toughening of the metamaterial. Indeed, localized heterogeneities can introduce mechanical dissipations in the network at various scales. The work of this project will consist in experiementally characterizing the mechanical properties of the metamaterials and to compare them to their homogeneous equivalent, and to describe their fracture resistance. Mechanical tests will be performed on an experimental setup conceived in the SPHYNX group. Analysis of the local and global deformation will be performed using different experiemental methods, in order to detect micro crack events with precision. An additionnal theoretical approach completed by numerical simulations based on fuse network and random beam models can also be discussed.
A strong interest for instrumentation and teamwork is requested for this project with a major experimental component. Proficiencies in experimental mechanics, material sciences and/or statistical physics are desirable. Some knowledge in modelization and numerical simulations are a bonus without being required. This project has both fundamental and applied interests and can help the student find prospects both in academia and in industrial opportunities.
Multiscale modeling of rare earth ion emission from ionic liquids under intense electric fields
The main objective of this thesis is to model the mechanisms of rare earth ion emission from ionic liquids subjected to an intense electric field, in order to identify the conditions favorable to the emission of weakly complexed ions.
The aim is to establish rational criteria for the design of new ILIS sources suitable for the localized implantation of rare earths in photonic devices.
The thesis work will be based on large-scale molecular dynamics simulations, reproducing the emission region of a Taylor cone under an electric field.
The simulations will be compared with emission experiments conducted in parallel by the SIMUL group in collaboration with Orsay Physics TESCAN, using a prototype ILIS source doped with rare earths. Comparisons of measurements (mass spectrometry, energy distribution) will enable the models to be adjusted and the proposed mechanisms to be validated.
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.
From Detector to Discovery: Constructing the ATLAS Inner Tracker and Probing Higgs Physics at the HL-LHC
This PhD project combines work on the construction of the new Inner Tracker (ITk) for the ATLAS experiment and an analysis of ATLAS sensitivity at the High-Luminosity LHC (HL-LHC) to key processes related to Higgs boson physics using ITk. The candidate will take part in the development, operation, and optimization of the test benches for ITk pixel modules at CEA. Together with two other partner laboratories in the Paris region, CEA will assemble and test about 20% of the ITk pixel modules. The student will contribute to the commissioning of the detector at CERN. The candidate will also carry out HL-LHC sensitivity studies of the interactions between the Higgs boson and the top quark, including for instance a CP-violation analysis in the ttH channel and an analysis of tH production, a process particularly sensitive to the Higgs–top and Higgs–W couplings. The first two years of the PhD are expected to be based at CEA Saclay, while the last year will be based at CERN.
V-SYNTHES-guided discovery of BET bromodomain inhibitors : a novel antifungal strategy against Candida auris
New antifungal strategies are urgently needed to combat Candida auris, an emerging multidrug-resistant fungal "superbug" responsible for severe hospital outbreaks and high-mortality infections. Our previous proof-of-concept studies in Candida albicans and Candida glabrata established that fungal BET bromodomains – chromatin-binding modules that recognize acetylated histones – represent promising new antifungal targets. We have developed an advanced set of molecular and cellular tools to accelerate antifungal BET inhibitor discovery, including FRET-based assays for compound screening, humanized Candida strains for on-target validation, and NanoBiT assays to monitor BET bromodomain inhibition directly in fungal cells.
This PhD project represents the translational next phase of our research program. It will exploit the AI-guided V-SYNTHES drug discovery approach – a cutting-edge virtual screening and design framework – to develop highly potent BET inhibitors targeting C. auris. Inhibitors will be profiled in biophysical, biochemical and cellular assays, structurally characterized in complex with their bromodomain targets, and validated for on-target activity in C. auris and antifungal efficacy in animal infection models. They will also be used to explore the emergence of resistance to BET inhibition. This project combines an original antifungal strategy with an innovative methodological approach, offering a unique framework for training in interdisciplinary and translational research.
Triplet superconductors: from weak to strong spin-orbit coupling
Since the 1980s, several unconventional superconductors have been discovered, some of which exhibit triplet pairing (total spin S=1) that may lead to interesting topological properties. Unlike singlet superconductors, their order parameter is a vector depending on the spin components (S_z=-1,0,1) and is strongly influenced by the crystal symmetry and the spin–orbit coupling (SO).
The thesis aims to study the transition between weak and strong spin–orbit coupling in a triplet superconductor, using a minimal multiband model inspired by the material CdRh2As3, where a field-induced triplet phase was recently observed. This research will enable the calculation of the dynamic spin susceptibility and the identification of possible collective spin resonances, similar to those seen in superfluid He3.
The project will mainly rely on analytical field-theoretical methods applied to condensed matter. It is intended for candidates with a solid background in quantum mechanics, statistical physics, and solid-state physics.
Cosmology with the Lyman-alpha forest from the DESI cosmological survey.
We use the large-scale distribution of matter in the universe to test our cosmological models. This is primarily done using baryon acoustic oscillations (BAO), which are measured in the two-point correlation function of this distribution. However, the entire matter field contains information at various scales, allowing us to better constrain our models than BAO alone. At redshifts greater than 2, the Lyman-alpha forest is the best probe of this matter distribution. The Lyman-alpha forest is a set of absorption lines measured in the spectra of distant sources. The large DESI spectroscopic survey has collected approximately one million of these spectra. Using the partial data set "DR2," we measured the BAO with an accuracy of 0.7%, which strongly constrains the expansion rate of the universe during the first billion years of its evolution.
This thesis aims to exploit the full set of large-scale Lyman-alpha data from DESI to obtain the strongest constraints on cosmological models possible. First, the student will apply a method known as reconstruction to improve the accuracy of BAO measurements by exploiting information from the matter density field. For the remainder of the thesis, the student will implement a new method known as simulation-based inference. Similar efforts have been carried out in our group with DESI galaxies. In this approach, the entire matter field is used directly to estimate cosmological parameters, particularly dark energy. Thus, the student will make an important contribution to DESI's final cosmological measurements with Lyman-alpha.
An internship is preferred before beginning this thesis.
Unbiased Shear Estimation for Euclid with Automatically Differentiable and GPU Accelerated Modeling
This PhD project focuses on achieving unbiased measurements of weak gravitational lensing — the tiny distortions in galaxy shapes caused by the matter along the line of sight. This technique is key to studying dark matter, dark energy, and gravity, and lies at the heart of the Euclid space mission launched in 2023. Traditional shape-measurement methods introduce systematic biases in shear estimation. The goal of this PhD is to develop and extend an innovative forward-modelling approach that directly infers the shear by simulating realistic galaxy images using deep-learning architectures. The student will adapt this framework to real Euclid data, accounting for the complexity of the Science Ground Segment (SGS) and implementing GPU-accelerated and high-performance computing solutions to scale to the full sky coverage. The project is timely, coinciding with Euclid’s first public data release in 2026. The expected outcome is a more accurate and robust shear estimation method, enabling the next generation of precision cosmology analyses.
Advanced methods of blockwise diffusion imaging for studying fetal cerebral development at the mesoscopic scale
The second half of pregnancy is an extremely rich period in terms of brain development, during which key processes such as neurogenesis, neuronal migration, and axonal growth take place; transient structures form and disappear, while brain volume increases more than tenfold. A blockwise ex-vivo imaging technique recently developed in NeuroSpin allows us to take a new look on developing brain tissues, leveraging ultra-high-field MRI at 11.7 teslas to acquire unprecedented whole-brain images at mesoscopic resolution (100 to 200 µm 3D isotropic) . The acquired data is highly multiparametric, including quantitative T1, T2, and T2* mapping, as well as high angular resolution, multi-shell diffusion-weighted imaging (b = 1500, 4500, 8000 s/mm² with 25, 60, and 90 directions respectively) at 200 µm isotropic resolution.
In order to reach such a high level of detail, a small-bore scanner is used (5 cm usable diameter) over extended scanning times (150 hours per field of view). Brains older than about 20 gestational weeks are too large, and are sectioned into blocks whose size is compatible with the scanner. The resulting blockwise images are registered using a dedicated semi-automatic protocol, and fused to reconstruct a set of whole-brain images. While this protocol has allowed us to obtain good-quality images on several fetal brain specimens (3 published, 3 other brains in progress as of the end of 2025), the diffusion imaging data remains to be fully analyzed: indeed, the blockwise nature of the acquisitions poses unique challenges, notably due to the discontinuity at the boundary between blocks, but also to non-linear image deformations and non-linearity of the magnetic field gradients.
The PhD candidate will be hosted in the inDEV team (imaging neurodevelopmental phenotypes) in close collaboration (co-supervision) with the Ginkgo team, which has leading expertise in diffusion imaging methods and has pioneered the blockwise acquisition technique in an adult brain known as Chenonceau. The PhD work lies at the interface between imaging, algorithmics, and developmental neuroscience: it will include developing and benchmarking new methods for processing this blockwise diffusion MRI to obtain high-quality tractography and fit diffusion microstructural models. It will also include an experimental part, where the PhD candidate will take part in the acquisition and reconstruction of new brains, both typical specimens and pathological ones with agenesis of the corpus callosum. Finally, the candidate will explore neuroscientific outcomes of this unprecedented dataset, which has exceptional potential to describe processes such as the development of subcortical pathways and associative white matter fibre tracts, and to become the first atlas of the developing fetal brain with fibre architecture at the mesoscopic scale.
Spectro-temporal analysis of Gamma-Ray Burst afterglows detected with SVOM
Gamma-Ray Bursts (GRB) are the most powerful explosions in the Universe. They last a few tens of seconds and emit the same amount of energy as the Sun during its entire lifetime. They gamma-ray emission is followed by a long lasting (hours to days) emission from the X-rays to the radio band. This "afterglow" emission is rich on information about the GRB nearby environnent and host galaxy. SVOM (Space based astronomical Variable Object Monitor) is a Sino-French mission, dedicated to GRB studies, and has been successfully launched in June 2024. It carries a multi-wavelength payload covering gamma-rays/X-rays/optical and includes two dedicated ground based robotic telescopes in Mexico and China.
The PHD project is focussed on the exploitation of the SVOM data for GRBs. The successful candidate will join the MXT science Teal at DAp. MXT is a new type of X-ray telescope, for which the DAp is responsible and its Instrument Centre is also hosted at DAp.
The PHD student will participate actively to the spectral and temporal analysis of MXT data. These data will be compared
to the other data acquired by the SVOM collaboration, especially in the optical an infrared domains.
This dataset will be used as a support to the physical interpretation of GRBs. More specifically, the aspects related to the modeling of the energy injection in the first phases of the afterglow will be used to determine the nature of the compact object at the origin of the relativistic flux, generating the electromagnetic emission observed.