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.

Reduction of reinforcement in reinforced concrete structures through nonlinear calculations and topological and evolutionary optimizations

Reinforcing steel plays a major role in the behavior of reinforced concrete structures. Nevertheless, significant conservatisms may sometimes be imposed by design codes, raising questions about the feasibility of construction or the viability of the structure (economic, environmental, etc.). It is within this context that the doctoral research takes place. Building on recent developments, the work aims to propose an innovative design approach relying on the use of nonlinear finite element calculations, combined with topological optimization algorithms (defining reinforcement directions and bar cross-sections) and evolutionary optimization algorithms (determining the placement of bars with fixed cross-sections).
The method should, through an iterative process, yield solutions that meet an optimal design configuration. Considering the multiple, potentially conflicting objectives to minimize (such as cost, feasibility, strength, and carbon footprint), the approach will guide the configuration of input parameters based on an analysis of the relevant output results.
Applying the method to complex, practice-based case studies (for example, beam-column junctions) will demonstrate its relevance compared with more conventional design methods. By the end of the thesis, the doctoral candidate will have developed advanced skills in the use and development of state-of-the-art tools, ranging from nonlinear finite element simulation to modern optimization techniques based on artificial intelligence.

High-Fidelity Monte Carlo Simulations of Neutron Noise in Nuclear Power Reactors

Operating nuclear reactors are subject to a variety of perturbations. These can include vibrations of the fuel pins and fuel assemblies due to fluid-structure interactions with the moderator, or even vibrations of the core barrel, baffle, and pressure vessel. All of these perturbations can lead to small periodic fluctuations in the reactor power about the stable average power level. These power fluctuations are referred to as “neutron noise”. Being able to simulate different types of in-core perturbations allows reactor designers and operators to predict how the neutron flux could behave in the presence of such perturbations. In recent years, many different research groups have worked to develop computational models to simulate these sources of neutron noise, and their resulting effects on the neutron flux in the reactor. The primary objective of this PhD thesis will be to bring Monte Carlo neutron noise simulations to the scale of real-world industry calculations of nuclear reactor cores, with a high-fidelity continuous-energy physics representation. As part of this process, the student will add novel neutron noise simulation capabilities to TRIPOLI-5, the next-generation production Monte Carlo particle-transport code jointly developed by CEA and ASNR, with the support of EDF.

Preconditioning of iterative schemes for the mixed finite element solution of an eigenvalue problem applied to neutronics

Neutronics is the study of the behavior of neutrons in matter and the reactions they induce, particularly the generation of power through the fission of heavy nuclei. Modeling the steady-state neutron flux in a reactor core relies on solving a generalized eigenvalue problem of the form:
Find (phi, keff) such that A phi=1/keff B phi and keff is the eigenvalue with the largest magnitude, where A is the disappearance matrix which is assumed invertible, B represents the production matrix, phi denotes the neutron flux, and keff is called the multiplication factor.

The neutronics code APOLLO3® is a joint project of CEA, Framatome, and EDF for the development of a next-generation code for reactor core physics to meet both R&D and industrial application needs [4].
The MINOS solver [2] is developed within the framework of the APOLLO3® project. This solver is based on the mixed finite element discretization of the neutron diffusion model or the simplified transport model. The strategy for solving the aforementioned generalized eigenvalue problem is iterative; it involves applying the inverse power method [6].

The convergence speed of this inverse power method algorithm depends on the spectral gap. In the context of large cores such as the EPR reactor, it is observed that the spectral gap is close to 1, which degrades the convergence of the inverse power method algorithm. It is necessary to apply acceleration techniques to reduce the number of iterations [7]. In neutron transport, the preconditioning called Diffusion Synthetic Acceleration is very popular for the so-called inner iteration [1] but has also recently been applied to the so-called outer iteration [3]. A variant of this method was introduced in [5] for solving a source problem. It is theoretically shown that this variant converges in all physical regimes.

[1] M. L. Adams, E. W. Larsen, Fast iterative methods for discrete-ordinates particle transport calculations, Progress in Nuclear Energy, Volume 40, Issue 1, 2002.

[2] A.-M. Baudron and J.-J. Lautard. MINOS: a simplified PN solver for core calculation. Nuclear Science and Engineering, volume 155(2), pp. 250–263 (2007).

[3] A. Calloo, R. Le Tellier, D. Couyras, Anderson acceleration and linear diffusion for accelerating the k-eigenvalue problem for the transport equation, Annals of Nuclear Energy, Volume 180, 2023.

[4] P. Mosca, L. Bourhrara, A. Calloo, A. Gammicchia, F. Goubioud, L. Mao, F. Madiot, F. Malouch, E. Masiello, F. Moreau, S. Santandrea, D. Sciannandrone, I. Zmijarevic, E. Y. Garcia-Cervantes, G. Valocchi, J. F. Vidal, F. Damian, P. Laurent, A. Willien, A. Brighenti, L. Graziano, and B. Vezzoni. APOLLO3®: Overview of the New Code Capabilities for Reactor Physics Analysis. Nuclear Science and Engineering, 2024.

[5] O. Palii, M. Schlottbom, On a convergent DSA preconditioned source iteration for a DGFEM method for radiative transfer, Computers & Mathematics with Applications, Volume 79, Issue 12, 2020.

[6] Y. Saad. Numerical methods for large eigenvalue problems: revised edition. Society for Industrial and Applied Mathematics, 2011.

[7] J. Willert, H. Park, and D. A. Knoll. A comparison of acceleration methods for solving the neutron transport k-eigenvalue problem. Journal of Computational Physics, 2014, vol. 274, p. 681-694.

Study of the behaviour of mixed oxide fuels with degrade isotopy at the beginning of life.

France has decided to adopt a 'closed' nuclear fuel cycle. This involves processing spent fuel to recover valuable materials such as uranium and plutonium, while other compounds such as fission products and minor actinides constitute final waste. UO2 fuel irradiated in pressurised water reactors (PWRs) is currently reprocessed to produce plutonium (PuO2), which is then reused in the form of mixed oxide (MOX) fuel. This fuel is then irradiated in PWRs, a process known as plutonium monorecycling. The CEA is currently studying the multi-recycling of materials using fuels containing Pu from the processing of spent MOX assemblies. However, this multi-recycled plutonium contains a higher proportion of highly alpha-active isotopes (Pu238, Pu240 and Pu241/Am241), resulting in more severe alpha self-irradiation than current MOX fuels experience [1]. This exacerbates certain physical phenomena [2-5], such as fuel swelling due to helium precipitation and the creation of crystal defects and decreased thermal conductivity [6-8], which can alter its behaviour in the reactor.
The proposed thesis will study the impact of these phenomena on the behaviour of MOX fuels at the beginning of the irradiation, using a combination of experimentation and modelling. Heat treatments will be employed to analyse the mechanisms of crystal defect healing and helium behaviour. Various experimental techniques will be employed to characterise the structure and microstructure (X-ray diffraction, scanning electron microscopy (SEM), Raman spectroscopy and microprobe analysis), defect densities (transmission electron microscopy (TEM)), helium release (KEMS), thermal gradient reproduction (CLASH laser) and thermal conductivity (LAF laser). The results will inform simulations modelling the microstructure and thermal properties.
This cross-disciplinary study will improve our understanding of the phenomena involved in the initial power-up of fuels damaged by alpha self-irradiation, particularly the impact of helium produced by decay.

You will be based at the Multi-Fuel Design and Irradiation Laboratory (LECIM) within the Research Institute for Nuclear Systems for Low-Carbon Energy Production at CEA/Cadarache. For the experimental part of the project, you will collaborate with the Chemical Analysis and Materials Characterisation Laboratory (LMAT) at CEA/Marcoule and the European Research Centre (JRC) in Karlsruhe. You will have the opportunity to publish your results through scientific publications and conference presentations. This role offers the chance to develop your expertise in a variety of techniques that can be applied across multiple fields of materials science and engineering.

[1]O. Kahraman, thésis, 2023.[2]M. Kato et al., J Nucl Mater, 393 (2009) 134–140.[3]L. Cognini et al., Nuclear Engineering and Design 340 (2018) 240–244.[4] T. Wiss et al., Journal of Materials Research 30 (2015) 1544–1554.[5]D. Staicu et al., J Nucl Mater 397 (2010) 8–18.[6] T. Wiss et al.,Front. Nucl. Eng. 4 (2025) 1495360.[7]E.P. Wigner, J. Appl. Phys. 17 (1946) 857–863.[8]D. Staicu et al., Nuclear Materials and Energy 3–4 (2015) 6–11.

From optimal control in NMR at 11.7 Tesla to precision imaging of the human brain in vivo

Parallel simulation and adaptive mesh refinement for 3D solids mechanics problems

The challenge of this PhD thesis is to implement adaptive mesh refinement methods for non-linear 3D solids mechanics adapted to parallel computers.

This research topic is proposed as part of the NumPEx (Digital for Exascale) Priority Research Programs and Equipment (PEPR). It is part of the Exa-MA (Methods and Algorithms for Exascale) Targeted Project. The PhD will take place at CEA Cadarache, within the Institute for Research on Nuclear Energy Systems for Low-Carbon Energy Production (IRESNE), as part of the PLEIADES software platform development team, which specializes in fuel behavior simulation and multi-scale numerical methods.

In finite element simulation, adaptive mesh refinement (AMR) has become an essential tool for performing accurate calculations with a controlled number of unknowns. The phenomena to be taken into account, particularly in solids mechanics, are often complex and non-linear: contact between deformable solids, viscoplastic behaviour, cracking, etc. Furthermore, these phenomena require intrinsically 3D modelling. Thus, the number of unknowns to be taken into account requires the use of parallel solvers. One of the current computational challenges is therefore to combine adaptive mesh refinement methods and nonlinear solid mechanics for deployment on parallel computers.

The first research topic of this PhD thesis concerns the development of a local mesh refinement method (of block-structured type) for non-linear mechanics, with dynamic mesh adaptation. We will therefore focus on projection operators to obtain an accurate dynamic AMR solution during the evolution of refined areas.

The other area of research will focus on the effective treatment of contact between deformable solids in a parallel environment. This will involve extending previous work, which was limited to matching contact meshes, to the case of arbitrary contact geometries (node-to-surface algorithm).

The preferred development environment will be the MFEM tool. Finite element management and dynamic re-evaluation of adaptive meshes require assessing (and probably improving) the efficiency of the data structures involved. Large 3D calculations will be performed on national supercomputers using thousands of computing cores.
his will ensure that the solutions implemented can be scaled up to tens of thousands of cores.

Modeling of a non-equilibrium dispersed phase and its fragmentation

In the context of the sustainable use of nuclear energy to produce carbon-free electricity, fourth-generation reactors, also known as "fast neutron" reactors, are necessary to close the fuel cycle.
This thesis falls within the framework of safety studies associated with such sodium-cooled reactors, and more particularly the hypothetical situation of a molten core relocating by gravity towards the core catcher at the bottom of the reactor vessel. A jet of corium (mixture of molten fuel and structural elements of the core) then interacts violently with the coolant, inducing, among other things, the fragmentation of the corium jet into droplets coupled with film boiling of the coolant. Characteristics of the resulting dispersed phase of corium and its fragmentation are crucial for studying the risk of runaway and steam explosion.
The aim of this thesis is to model a dispersed phase and its fragmentation in a surrounding fluid, using an approach that is both efficient and able to account to the scale variations and thermal imbalances between the droplets and the carrier phase. The method considered to meet these objectives is the method of moments, which derives from a kinetic model. It requires adequate closure and numerical schemes that satisfy non-standard constraints, while offering, in return, a crucial cost/accuracy compromise in the context studied. The advancements will be a priori implemented in the CFD software SCONE, built on the CEA's open-source TRUST platform.
The main work location will be based at the LMAG (Laboratory of Severe Accidents Modeling) at the IRESNE Institute of CEA Cadarache. Part of the work will also be carried out at the EM2C Laboratory (Molecular and Macroscopic Energetics, Combustion) – CNRS/CentraleSupélec in Paris.
The future PhD will work in a scientific dynamic environment and will acquire skills enabling to aspire to academic and industrial R&D positions.

Keywords : Dispersed Phase, Fragmentation, Kinetic, Method of Moments, Multiphase, Numerical methods, Severe Accidents.

UO2 Powders: Morphological Characterization of Aggregates and Study of Their Interactions Using a Combined Experimental and numerical Approach

This PhD thesis is part of the optimization of nuclear fuel fabrication processes, which rely on the powder metallurgy of uranium dioxide (UO2) and plutonium dioxide (PuO2). These powders exhibit a hierarchical microstructure composed of crystallites forming rigid aggregates, themselves agglomerated into larger structures. The morphology and interactions between aggregates play a key role in the macroscopic behavior of the powders—particularly their flowability, compressibility, and agglomeration capacity—and directly influence the quality of the fuel pellets obtained after pressing and sintering. However, the experimental characterization of these aggregates remains complex and does not yet allow for the establishment of a predictive link between synthesis processes and morphological properties.
The objective of this thesis is to combine experimental and numerical approaches to achieve a detailed characterization of the aggregates in a reference powder. Experimentally, techniques such as Scanning Electron Microscopy (SEM), specific surface area measurement (BET), and laser granulometry will be used to determine particle size, roughness, and size distribution. In parallel, numerical simulations based on the Discrete Element Method (DEM) will be employed to construct a granular digital twin consistent with the experimentally measured properties. This digital twin will allow the reconstruction of the internal structure of the aggregates, the evaluation of interparticle adhesion forces, and the analysis of agglomeration and densification phenomena under controlled conditions.
The PhD will take place at CEA Cadarache within the Institute for Research on Nuclear Systems for Low-Carbon Energy Production (IRESNE). The student will be assigned to the PLEIADES Fuel Development Laboratory (LDOP), which specializes in simulating nuclear fuel behavior (from fabrication to in-reactor performance) and in multi-scale numerical methods. The work will be carried out in collaboration with the CNRS/LMGC in Montpellier, internationally recognized for its research on granular materials, and with the Uranium Fuel Laboratory (LCU – CEA Cadarache), which has extensive experience in the experimental characterization of uranium powders.
The PhD candidate is expected to demonstrate strong skills in numerical simulation and in the physical analysis of results. He will share its results through publications and conference presentations and will have the opportunity to learn or further develop various experimental and numerical techniques that can be applied in other contexts.In particular, the issues related to the physics of granular media — which constitute the core of this PhD — are of significant industrial relevance and are common to many other sectors handling powders, such as pharmaceuticals, agri-food, and powder metallurgy.

[Hebrard2004] S.Hebrard, Etude des mécanismes d’évolution morphologique de la structure des poudres d’UO2 en voie sèche, thèse de doctorat, CEA-LSG2M-COGEMA), 2004.

[Pizette2010] P. Pizette, C.L. Martin a, G. Delette, P. Sornay, F. Sans, Compaction of aggregated ceramic powders: From contact laws to fracture and yield surfaces, Powder Technology, 198, 240-250, 2010.

[Tran2025] T.-D. Tran , S. Nezamabadi , J.-P. Bayle, L. Amarsid, F. Radjai , Effect of interlocking on the compressive strength of agglomerates composed of cohesive nonconvex particles, Advanced Powder Technology 36, 2025.

Numerical Simulation of Fluid–Structure Interactions with Contact under Flow Using a Penalized Direct Forcing Method

This PhD work is part of the study of the dynamics of fuel assemblies subjected to axial flow and external mechanical excitation, particularly of seismic type. The objective is to develop an innovative numerical approach capable of accurately predicting the three-dimensional dynamic response of one or several assemblies, while accounting for the coupled effects between the fluid flow and mechanical loads. This problem is particularly complex due to the need to consider large displacements, potential contacts between structures, and strong interactions with the surrounding fluid.