Measurement and modelling of the chemical activity of complex fluid components in hydrometallurgy
Modern extraction processes rely on the optimal use of complex fluids, the detailed understanding of which remains too empirical. To overcome this, new multi-scale simulation software packages are being developed, with one of the unknowns at the mesoscopic scale, where the aggregation of molecules, interface structures, etc. are not well understood. Chemical activity is key here, as it controls exchange and transfer processes. Understanding it allows these software packages to be validated. It must therefore be possible to measure and analyse it reliably for each component, particularly volatile ones. We proposed to do this by measuring their partial pressures. An initial version of a microfluidic device was developed and patented, which allows the partial pressures of volatile components to be measured simultaneously by infrared spectroscopy in a hollow waveguide. This experimental prototype device has been validated on simple systems. The aim of this thesis is to demonstrate the application potential of this unique tool for the simulation and rapid development of processes, focusing on important concrete cases, both from an experimental and modelling point of view. This type of study would be completely new and would make it possible to experimentally verify the stability predictions of complex fluids for the first time.
The PhD student will first need to update the microfluidic brick. He/she will then use it to measure the chemical activities of the aforementioned complex fluids and will work with Jean-François Dufrèche to test/validate/further develop the software packages. Secondly, at NTU in Singapore and under the co-supervision of Professor Alex Yan Qingyu (https://personal.ntu.edu.sg/alexyan/ ), he/she will use the duplicate microfluidic platform currently being assembled to apply these results to the rapid development of a process for extracting a critical metal from recycled electronic components from printed circuit boards (SCARCE joint laboratory).
Expected results: publications, proprietary software package and possible patents on the new processes developed.
Uncovering the signaling roles of inositol polyphosphates in plant growth and development
Inositol polyphosphates (InsPs), particularly their pyrophosphate derivatives (PP-InsPs), are recently characterized as signaling molecules present in all eukaryotes. Extensive research has been conducted on the PP-InsP pathway revealing its impacts on organogenesis and various diseases such as cancer metastasis, obesity, and diabetes. Cellular PP-InsPs exist in low concentrations, complex isoforms, and turnover fast, therefore, making them a real challenge to monitor and to analyze. This restricts the PP-InsP study especially on defining their specific roles or putatively variable distribution among cells/tissues. To solve the problem, this project aims to create cellular reporters for monitoring PP-InsPs in real-time. Given the PP-InsP pathway is conserved, the development of the PP-InsP sensors in plants will have a broader impact on the study of to the fundamental characteristics of PP-InsP signaling in animals. For example, the transfer of the PP-InsP reporters to cancer cell lines for possibility to use it for better understanding of PP-InsP-regulated cancer metastasis in the future.
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.