Non-invasively exploring the cerebellum microstructure with magnetic resonance
To better diagnose and monitor brain diseases, we need “non-invasive biopsies” to access the tissue cell-type composition and state without opening the skull. Magnetic resonance imaging (MRI) research efforts attempt to tackle the challenge but often lack cellular specificity because of the ubiquitous nature of water. Diffusion-weighted magnetic resonance imaging (dMRS) measures diffusion of intracellular and partly cell specific molecules in a region of interest, and forms a solid basis for resolving cell-types non-invasively. Among challenges, resolving signal contributions from the different cerebellar neurons could help monitor and understand neurodevelopmental and ataxic disorders. The cerebellum is a brain region representing 10% of the brain volume but containing more than half of the brain neurons, with the very large and complex Purkinje cells and the very small and round granule cells, both having very different functions and metabolism. The PhD project aims to disentangle these cells with complementary strategies: a classical dMRS approach and a quantum dMRS approach confronted to the state-of-the-art microstructure MRI methods.
Role of the JMY protein in human brain development and glioblastoma stem cell radioresistance: from brain organoids to therapeutic screening
The JMY protein is an important regulator of the actin cytoskeleton, involved in cell migration and morphogenesis. Expressed in the developing brain, it is associated with several key processes of neurogenesis, including neurite formation, dendritogenesis, myelination, and neuronal migration. However, its specific role in human brain development remains poorly characterized.
In parallel, our work demonstrates that JMY plays a central role in the pathophysiology of glioblastoma, a highly aggressive brain tumor. Following irradiation, glioblastoma stem cells increase their migratory and invasive capacities through a pathway involving HIF1a and JMY. This activation promotes the formation of actin-rich structures known as tumor microtubes, which are associated with therapeutic resistance.
This project aims to investigate JMY as a common regulator of neurodevelopment and tumor plasticity.
In a first axis, we will analyze the impact of JMY deficiency in human brain organoids derived from iPS cells, in order to assess its effects on proliferation, differentiation, neurogenesis, and cortical organization.
In a second axis, a high-throughput pharmacological screening will be conducted to identify inhibitors capable of blocking radiation-induced migration of glioblastoma tumor stem cells.
The expected results will improve our understanding of JMY’s role in the human brain and support the development of new strategies aimed at limiting glioblastoma recurrence after radiotherapy.
From Few-body to High-Energy antinuclei Collision Kinematics
Because rare antinuclei in space could carry information about exotic production mechanisms—including, potentially, dark-matter annihilation or decay—their study has become a high-impact frontier connecting nuclear physics, astroparticle physics, and collider measurements. Interpreting present and future antinuclei searches, however, is limited by a lack of key nuclear input data: low-energy scattering, annihilation, and breakup processes of antinuclei on ordinary matter are difficult to measure directly, precisely because producing and manipulating antinuclei is so challenging. This motivates a complementary, theory-driven strategy. Our project adopts a bottom-up approach: we will establish a controlled, ab initio description of the simplest low-energy antimatter nuclear systems and collisions, identify the underlying many-body mechanisms of annihilation, and then propagate these constraints to transport and event-level modeling at the many-body and higher-energy scales. In doing so, we aim to both deepen our understanding of matter–antimatter interactions at the nuclear level and deliver validated inputs for the simulation tools used in astroparticle and collider applications.
Two-way transfer between the two fields: In this project, we simplify the problem to the simplest case that can be treated by the ab initio method: in INCL the annihilation of the antideuteron is identified as an annihilation with a quasi-deuteron in a large target. Two key questions must be addressed in part using ab initio calculations:
1. Which quasi-deuteron will interact?
2. Which output channel will result?
Gyrokinetic modelling of the nonlinear interaction between energetic particle-driven instabilities and microturbulence in tokamak plasmas
Tokamak plasmas are strongly nonlinear systems far from thermodynamic equilibrium, in which instabilities of very different spatial scales coexist, ranging from large-scale macroscopic oscillations to microturbulence. The presence of energetic ions produced by fusion reactions or by auxiliary heating further enhances these instabilities through wave–particle resonances. Microturbulence is responsible for heat and particle transport in the thermal plasma, while instabilities driven by energetic particles can induce their radial transport and, consequently, their losses. Both phenomena degrade the performance of present tokamak plasmas, and possibly also those of burning plasmas such as ITER.
Recent results, however, show that these instabilities, which have long been studied separately, can interact nonlinearly, and that this interaction may lead to an unexpected improvement of plasma confinement.
The objective of this project is to investigate these multiscale interactions using the gyrokinetic code GTC, which is able to simultaneously simulate turbulence and energetic-particle-driven instabilities. This work aims to improve the understanding of the nonlinear mechanisms governing plasma confinement and to identify optimal regimes for future fusion plasmas.
The multiple roles of cohesin in genome stability
Cohesin, a ring-shaped protein complex, is crucial for genome stability, gene expression, sister chromatid cohesion, and DNA repair. It forms intrachromosomal loops during interphase, aiding in chromatin organization by bringing enhancers and promoters together. Cohesin also ensures sister chromatid cohesion during DNA replication and repairs double-strand breaks (DSBs). In response to DNA damage, cohesin binds to DSBs and enhances cohesion via damage-induced cohesion (DI-cohesion). Our recent findings show that cohesin tethers DSB ends through oligomer formation (Phipps et al., 2025).
This research project aims, in the frame of an ANR funded project, to explore how DNA damage influences cohesin’s functions in genome stability. The main hypothesis is that DNA damage activates distinct cohesin populations with specific roles critical for maintaining genome integrity. Using Saccharomyces cerevisiae as a model, the project focuses on three goals: analyzing the impact of DNA damage on cohesin composition and modifications, studying oligomerization in DSB tethering, and identifying the cohesin populations involved in DI-cohesion.
The methodology combines biochemical, genetic, and genomic approaches. Key tasks include identifying new cohesin interactors, analyzing cohesin in specific mutants, and investigating post-translational modifications.
This project aims to provide comprehensive insights into cohesin’s diverse roles in genome stability beyond traditional sister chromatid cohesion.
Modelling the redshift distribution of Euclid’s lensed galaxies for field-level analyses
The Euclid mission will deliver weak lensing data with unprecedented precision, which has the potential to revolutionise our understanding of dark energy and the growth of cosmic structures. Extracting its full information content requires going beyond the standard analyses. To make optimal use of the data, the OCAPi project will analyse Euclid's lensing maps directly at the pixel level. This approach, known as field-level inference, captures all the information and provides up to 5 times better constraints on the cosmological parameters (Porqueres et al. 2022, 2023).
This increased precision, however, requires an accurate modelling of the data. One of the main calibration challenges in weak lensing surveys is the redshift distribution of the lensed galaxies. Current calibration methods were designed for the standard analyses and may not be sufficiently accurate for field-level techniques. Quantifying the accuracy requirements and developing methods capable of reaching it is essential to enable field-level analyses of Euclid data and unlock the full scientific potential of the survey.
The goal of this PhD project is to develop a new redshift sampler for weak lensing, designed to meet the accuracy requirements of field-level inference. This sampler will combine physical models of galaxy populations with flexible machine-learning techniques. The thesis will contribute to maximising the potential of Euclid's weak lensing data and advance our understanding of the formation of cosmic structures.
Optimising the enzymatic degradation of polylactic acid (PLA) to produce biohydrogen (BioH2) through photofermentation.
This thesis project presents a novel method of producing biohydrogen (BioH2) through the enzymatic breakdown of polylactic acid (PLA), a bioplastic which is challenging to recycle. The aim is to optimise the hydrolysis of PLA into lactic acid, which can be metabolised directly by purple non-sulfur bacteria (PNSB) to produce BioH2 in anoxic conditions. The work will entail selecting high-performance esterases in collaboration with Génoscope CEA, expressing them in soluble form in model hosts such as E. coli, yeasts and PNSB, and optimising reaction conditions such as pH, temperature and concentration to maximise lactic acid production. The second phase will focus on enhancing photofermentation in a photobioreactor (PBR) with advanced control systems (LED, AI and CFD). Funded by the CEA and PUI Grenoble Alpes, this project is part of a circular economy approach, aiming to develop a scalable process for converting PLA waste into renewable energy in line with the challenges of the energy transition.
Resilience of fusion plasmas in a metallic environment, from WEST to ITER
Magnetic confinement nuclear fusion is an attractive option for contributing to the future energy mix, and the ITER project will, in the coming decade, mark a new milestone in the scientific and technological development of this field by producing more fusion energy than the energy deposited to sustain it. However, in a fusion power plant, the wall of the combustion chamber will be subjected to strong thermal and neutron stresses and must also limit the trapping of hydrogen isotopes used in the nuclear reaction.
The material considered the best compromise is tungsten, a metal whose high melting point and lack of chemical affinity with hydrogen are its main advantages. However, its high atomic number makes it highly radiative in the plasma where the reactions occur, which is detrimental to energy confinement and overall performance. It is therefore crucial to understand—both on current machines and through simulations for ITER—the impact of the inevitable tungsten dust (observed in the WEST tokamak) on turbulent transport, magneto-hydrodynamic stability, and ultimately on achieving a viable scenario for nuclear fusion. These aspects will form the foundation of the PhD project, combining experimental analysis on WEST at CEA with validation through simulations that include all relevant aspects, and extrapolation to the ITER environment. This work will be carried out in collaboration with ITER, the UKAEA (United Kingdom) for the simulation code, the CNR-Milano team for the tungsten dust trajectory, and the CEA teams at the IRFM.
In situ and real-time characterization of nanomaterials by plasma spectroscopy
The objective of this Phd is to develop an experimental device to perform in situ and real time elemental analysis of nanoparticles during their synthesis (by laser pyrolysis or flame spray pyrolysis). Laser-Induced Breakdown Spectroscopy (LIBS) will be used to identify the different elements present and their stoichiometry.
Preliminary experiments conducted at LEDNA have shown the feasibility of such a project and in particular the acquisition of a LIBS spectrum of a single nanoparticle. Nevertheless, the experimental device must be developed and improved in order to obtain a better signal to noise ratio, to increase the detection limit, to take into account the different effects on the spectrum (effect of nanoparticle size, complex composition or structure), to automatically identify and quantify the elements present.
In parallel, other information can be sought (via other optical techniques) such as the density of nanoparticles, the size or shape distribution.
Elliptic Flow of Charmed Hadrons in Heavy-Ion Collisions at LHCb?
The FLOALESCENCE project explores one of the most fundamental questions in Quantum Chromodynamics (QCD): how quarks and gluons transition from a deconfined Quark–Gluon Plasma (QGP) into ordinary hadrons.?This transition, called hadronization, occurred microseconds after the Big Bang and can be recreated today in ultra-relativistic lead–lead collisions at CERN’s Large Hadron Collider (LHC).
The PhD will focus on charm quarks—excellent probes of the QGP because they are produced early in the collision and interact throughout its evolution. Using the LHCb detector, uniquely sensitive in the forward rapidity region, the project aims to measure the elliptic flow (v2) of charmed baryons (?c+) and mesons (D0) in Pb–Pb collisions.?The goal is to test whether these heavy quarks thermalize and hadronize through a coalescence mechanism, a key feature of QGP dynamics.
Objectives and tasks:
- Extract and analyze ?c+ and D0 signals in newly collected 2024–2025 Pb–Pb datasets at LHCb.
- Implement a novel flow analysis method (based on the reformulated Lee–Yang Zeros approach) for the first time at LHCb.
- Develop an event-by-event multiplicity metric to correlate flow with system energy density.
- Compare results to theoretical models and cross-check with measurements at central rapidity (ALICE).
- Publish results and present findings at international conferences.
The successful candidate will:
- Develop advanced data-analysis expertise with CERN’s LHCb software framework, ROOT, and machine learning–based signal extraction.
- Gain in-depth knowledge of QCD and relativistic heavy-ion physics, especially QGP properties and collective phenomena.
- Learn modern statistical methods for flow analysis and uncertainty estimation.
- Acquire collaborative and communication skills within a major international experiment (LHCb), including presentations in collaboration meetings and conferences.
- Build strong experience in scientific computing, big-data handling, and detector physics, valuable for both academic and industry careers.