PtSeipin : linking lipid droplets biogenesis and degradation in the diatom Phaeodactylum tricornutum
Microalgae encompass a wide diversity of organisms and have attracted increasing interest due to their ability to produce biomolecules of biotechnological and industrial relevance. In particular, they can accumulate oil within lipid droplets (LDs) in response to abiotic stresses such as nitrogen deprivation. This oil accumulation holds great potential for biofuel production.We recently demonstrated that knockout of the gene encoding Seipin, a protein involved in LD biogenesis, leads to a strong oil accumulation in the diatom Phaeodactylum tricornutum. Moreover, this accumulation appears to result from an absence of LD degradation in the Seipin-deficient mutants. These findings suggest that, in this diatom, LDs are programmed to undergo degradation soon after their formation, thus inhibiting LD degradation could prove a promising strategy to increase their oil content.This project aims to elucidate the mechanisms underlying LD degradation and, more specifically, the connections between their biogenesis and degradation. Three main research axes will be pursued:
1. Identify PtSeipin interaction partners involved in LD degradation, using both candidate-based and unbiased approaches.
2. Characterize the LD degradation pathways disrupted in PtSeipin knockout mutants by combining electron microscopy with transcriptomic and proteomic analyses.
3. Investigate how microalgae utilize oil during the recovery phase after stress, through fluxomic approaches.
Euclid Weak Lensing Cluster Cosmology inference
Galaxy clusters, which form at the intersection of matter filaments, are excellent tracers of the large-scale matter distribution in the Universe and are a valuable source of information for cosmology.
The sensitivity of the Euclid space mission (launch in 2023) allow blind detection of galaxy clusters through gravitational lensing (i.e. directly linked to the projected total mass). Combined with its wide survey area (14,000 deg²), Euclid should allow the construction of a galaxy cluster catalogue that is unique in both its size and selection properties.
In contrast to existing cluster catalogues, which are typically based on baryonic content (e.g., X-ray emission from intra-cluster gas, the Sunyaev-Zel’dovich effect in the millimeter regime, or optical emission from galaxies), a catalogue derived from gravitational lensing is directly sensitive to the total mass of the clusters. This makes it truly representative of the underlying cluster population, a significant advantage for both galaxy cluster studies and cosmology.
In this context, we have developed a multi-scale detection method specifically designed to identify galaxy clusters based only on their gravitational lensing signal, which has been pre-selected to produce the Euclid cluster catalogue.
The goal of this PhD project is to build and characterize the galaxy cluster catalogue identified via weak lensing in the data collected during the first year of Euclid observations (DR1), based on this detection method. The candidate will derive cosmological constraints from the modelling of the cluster abundance, using the classical Bayesian framework, and will also investigate the potential of Simulation-Based Inference (SBI) methods for cosmological inference.
Development of a Modular Enzymatic Platform for the In Silico Design and Synthesis of Novel Therapeutic Peptides via Protein Splicing
The rise of antimicrobial resistance (AMR) has developed into a slow-moving epidemic, fueled by the overuse and misuse of antibiotics, coupled with a stagnation in the development of new antimicrobial agents over the past four decades. Addressing this crisis requires not only more judicious use of existing antibiotics but also the development of innovative drugs capable of overcoming resistant pathogens. In this context, the abundant genomic data generated in the omics era has facilitated the resurgence of natural products as a vital source of novel compounds. Among these, natural peptides—with their unique and diverse chemical properties—have garnered particular interest as potential antibiotics, anticancer agents, and inhibitors targeting specific pathological processes.
The aim of this PhD project is to develop a novel, modular enzymatic tool that enables the in silico design and synthesis of peptides with unprecedented chemical diversity. Central to this approach is the exploitation of a unique chemical reaction: protein splicing. This innovative reaction allows precise removal or editing of specific peptidic sequences, thereby providing a powerful platform to generate hybrid peptides with tailored functionalities, including potential therapeutic agents.
This project will integrate structural and functional studies, computational peptide design and enzyme engineering, aiming to expand the chemical and functional diversity of peptide-based molecules. The successful candidate will work in a state-of-the-art research setting, equipped with cutting-edge facilities and collaborative opportunities, fostering innovative approaches and impactful contributions to the field.
Photo- and thermocatalytic cross-coupling of esters for the synthesis of biosourced alkenes
The easy access to energy and carbon-based raw materials offered by the fossil feedstock allowed a rapid growth of our society. Nevertheless, the expected depletion of fossil resources and climate change, require changing for a more sustainable model. Bio-based feedstock is a promising source of carbon to substitute petrochemicals but require a drastic change of the actual model. While the current paradigm relies on the production of energy and high-value molecules through oxidation steps, a model based on Carbon Circular Economy, i.e. the transformation of CO2 and biomass feedstock that are already highly oxidized materials demands the development of new methodologies for reduction, deoxygenation, and the direct use of oxygenated bonds to access functionalized and useful organic molecules.
In organic chemistry, cross-coupling reactions represent one of the major tools to create C–C bonds. However, they are still based mainly on the use of organic halides as electrophiles. In this project, the PhD candidate will demonstrate that readily available and abundant alkyl esters can serve as electrophilic coupling partners in catalyzed cross-coupling reactions with alkenes. Esters can indeed be directly biosourced or easily synthesized from alkyl carboxylic acids and alcohols, thereby diminishing the environmental impact of the carbon-carbon bond formation.
Cosmological parameter inference using theoretical Wavelet statistics predictions
Launched in 2023, the Euclid satellite is surveying the sky in optical and infrared wavelengths to create an unprecedented map of the Universe's large-scale structure. A cornerstone of its mission is the measurement of weak gravitational lensing—subtle distortions in the shapes of distant galaxies. This phenomenon is a powerful cosmological probe, capable of tracing the evolution of dark matter and helping to distinguish between dark energy and modified gravity theories.
Traditionally, cosmologists have analyzed weak lensing data using second-order statistics (like the power spectrum) paired with a Gaussian likelihood model. This established approach, however, faces significant challenges:
- Loss of Information: Second-order statistics fully capture information only if the underlying matter distribution is Gaussian. In reality, the cosmic web is highly structured, with clusters, filaments, and voids, making this approach inherently lossy.
- Complex Covariance: The method requires estimating a covariance matrix, which is both cosmology-dependent and non-Gaussian. This necessitates running thousands of computationally intensive N-body simulations for each model, a massive and often impractical undertaking.
- Systematic Errors: Incorporating real-world complications—such as survey masks, intrinsic galaxy alignments, and baryonic feedback—into this framework is notoriously difficult.
In response to these limitations, a new paradigm has emerged: likelihood-free inference via forward modelling. This technique bypasses the need for a covariance matrix by directly comparing real data to synthetic observables generated from a forward model. Its advantages are profound: it eliminates the storage and computational burden of massive simulation sets, naturally incorporates high-order statistical information, and can seamlessly integrate systematic effects. However, this new method has its own hurdles: it demands immense GPU resources to process Euclid-sized surveys, and its conclusions are only as reliable as the simulations it uses, potentially leading to circular debates if simulations and observations disagree.
A recent breakthrough (Tinnaneni Sreekanth, 2024) offers a compelling path forward. This work provides the first theoretical framework to directly predict key wavelet statistics of weak lensing convergence maps—exactly the kind Euclid will produce—for any given set of cosmological parameters. It has been shown in Ajani et al (2021) that the wavelet coefficient L1-norm is extremely powerful to constraint the cosmological parameters. This innovation promises to harness the power of advanced, non-Gaussian statistics without the traditional computational overhead, potentially unlocking a new era of precision cosmology. We have demonstrated that this theoretical prediction can be used to build a highly efficient emulator (Tinnaneri Sreekanth et al, 2025), dramatically accelerating the computation of these non-Gaussian statistics. However, it is crucial to note that this emulator, in its current stage, provides only the mean statistic and does not include cosmic variance. As such, it cannot yet be used for full statistical inference on its own.
This PhD thesis aims to revolutionize the analysis of weak lensing data by constructing a complete, end-to-end framework for likelihood-free cosmological inference. The project begins by addressing the core challenge of stochasticity: we will first calculate the theoretical covariance of wavelet statistics, providing a rigorous mathematical description of their uncertainty. This model will then be embedded into a stochastic map generator, creating realistic mock data that captures the inherent variability of the Universe.
To ensure our results are robust, we will integrate a comprehensive suite of systematic effects—such as noise, masks, intrinsic alignments, and baryonic physics—into the forward model. The complete pipeline will be integrated and validated within a simulation-based inference framework, rigorously testing its power to recover unbiased cosmological parameters. The culmination of this work will be the application of our validated tool to the Euclid weak lensing data, where we will leverage non-Gaussian information to place competitive constraints on dark energy and modified gravity.
References
V. Ajani, J.-L. Starck and V. Pettorino, "Starlet l1-norm for weak lensing cosmology", Astronomy and Astrophysics, 645, L11, 2021.
V. Tinnaneri Sreekanth, S. Codis, A. Barthelemy, and J.-L. Starck, "Theoretical wavelet l1-norm from one-point PDF prediction", Astronomy and Astrophysics, 691, id.A80, 2024.
V. Tinnaneri Sreekanth, J.-L. Starck and S. Codis, "Generative modeling of convergence maps based in LDT theoretical prediction", Astronomy and Astrophysics, 701, id.A170, 2025.
Real-space fitting of flexible molecular structures in high-speed AFM topographic movies
Structural biology seeks to understand the function of macromolecules by determining the precise position of their atoms. Its traditional methods (X-ray crystallography, NMR, electron microscopy), although effective, offer a static view of macromolecules, limiting the study of their dynamics. A new paradigm is emerging: integrative structural biology, combining several techniques to capture, among other things, molecular dynamics. However, despite improvements in femtosecond serial crystallography, molecular dynamics simulations, and cryo-electron tomography, current methods struggle to reach the functional time scale (milliseconds to seconds).
The advent of new scanning probe microscopy, and in particular the recent development of high-speed atomic force microscopy (HS-AFM), allows molecular movements to be observed on the millisecond scale, but lacks the atomic resolution to revolutionize structural biology. The objective of the proposed topic is to further exploit the use of HS-AFM by modeling detailed atomic structures at the heart of the images obtained. The tasks will be both biophysical and computational, involving the improvement of the existing AFM-Assembly tool, which allows direct spatial adjustment of the atomic coordinates of the target molecule under AFM topography. The aim is to apply this protocol to a new type of big data, namely topographical movies obtained by high-speed AFM.
The thesis will be conducted at the Institute of Structural Biology in Grenoble, within the Methods and Electron Microscopy (MEM) group of the Grenoble Interdisciplinary Research Institute (IRIG). It will be carried out in collaboration with the DyNaMo laboratory in Marseille, which specializes in high-speed AFM data acquisition, as part of a joint ANR funding application.
The scientific interest of the project is major for modern integrative structural biology. The great scientific challenge of the coming years in structural biology is the study and analysis of molecular dynamics, in order to move beyond the current paradigm (instantaneous photography) and participate in the emergence of a new paradigm (real-time movie).
Deep UV-LEDs based on digital alloys (GaN)n/(AlN)m
Context :
Group-III nitride semiconductors (GaN, AlN, InN) are renowned for their outstanding light emission properties. For more than two decades, they have powered the blue and white LEDs used worldwide, thanks to highly efficient InGaN quantum wells (external quantum efficiency > 80%). In contrast, UV LEDs based on AlGaN quantum wells are still very inefficient (< 10%) and only recently became commercially available. Overcoming this limitation is a key challenge in optoelectronics: achieving efficient deep-UV emission (220–280 nm) would enable high-performance bactericidal applications such as water purification, surface sterilization, and virus inactivation.
Recently, two breakthrough concepts are promising to explore for UV-LEDs:
1. Deep-UV emission from GaN monolayers in AlN: Grow a few atomic monolayers (MLs) of GaN embedded in an AlN matrix. This extreme quantum confinement leads to deep-UV emission down to 220 nm. High emission efficiency is expected due to strong exciton binding, stable even at room temperature
2. Enhanced doping using graded digital GaN/AlN alloys: Use graded digital alloys (GaN)?/(AlN)? where n and m are the number of atomic layers. This architecture enables efficient n- and especially p-type doping, which is a major bottleneck in AlGaN. GaN is much easier to dope than AlN, making this approach very promising for device fabrication.
Scientific Targets :
The aim is to master monolayer growth using MOVPE (metal-organic vapor phase epitaxy), the most industrially relevant technique :
- M2 project: develop the growth of GaN monolayers on AlN substrates, study their deep-UV emission properties, and optimize growth conditions for self-limited single-layer deposition.
- PhD continuation: design and fabricate doped digital GaN/AlN alloys to build the first efficient deep-UV LEDs based on this architecture.
Lab background and collaboration:
The group has long-standing expertise in visible and UV light emission from nitride nanowires. We have already demonstrated 280 nm emission from (GaN)?/(AlGaN)? digital alloys, proving the viability of this approach. The project will be highly experimental (epitaxy, advanced structural and optical characterization) and conducted in close collaboration with Institut Néel for cathodoluminescence analysis and device processing.
Why join this project ?
Gain expertise in epitaxy, semiconductor physics, and optoelectronics. Work in a dynamic, collaborative environment with strong ties to industry. Contribute to the development of the next generation of deep-UV LEDs.
Exploration of VACNTs in Anode-less Batteries: Mechanism and Cell Optimization
Anode-less or anode-free batteries are getting increasing attention owing to their excellent energy density, cost efficiency, and ease of process upscaling. Exploring anode-less battery will offer a breakthrough in energy storage devices by using the lithium reserve already present in the NMC cathode to reversibly cycle after an initial formation process, which will reduce the overall thickness, processing steps, and cost of materials, and provide excellent energy density. Vertically aligned CNTs (VACNTs) on metal substrates can be an interesting choice for this application due to their low thickness, reproducible synthesis process, and uniform surface properties, which have already proven their applicability in supercapacitors. In this PhD project, we will investigate their newer avenue of applications- anode-less batteries, where VACNTs act as the lithium or sodium plating substrate. We will study the electrochemistry of VACNT in lithium anode-less batteries (in liquid and solid electrolytes) and in sodium anode-less batteries in a liquid electrolyte. The PhD student will work on the synthesis optimizations of VACNT to tune the thickness and density to match their electrochemistry. Post-cycling studies (Raman and SEM) will be carried out to study the effect of cycling and the electrolytes on the VACNT layers. The project aims to explore the possibility of the application of VACNTs in various energy storage systems, which can open up new application possibilities and valorization
LOW THERMAL CONDUCTIVITY MECHANISMS IN RARE-EARTH OXIDES
Understanding the parameters which determine the magnitude of thermal conductivity (k) in solids is of both fundamental and technological interests. k is sensitive to all quasiparticles carrying energy, whether charged or neutral. Foremost among these are phonons, the collective vibrations of atoms in crystals. Measurements of k, however, have also identified more exotic carriers like spinons in the antiferromagnetic Heisenberg chain. In terms of applications, thermal properties of solids are at the heart of major social and environmental issues. The need, for instance, for highly efficient thermoelectric and thermal barrier devices to save energy has driven the quest for low thermal conductors. Over time, a range of strategies has thus been suggested to hinder phonon velocities and/or mean free paths: use of weak interatomic bonds, strong anharmonicity, nanoscale designs, or complex or disordered unit cells. Another promising concept to further impair the phonon mean-free path is based on magneto-elastic coupling.
Still in its infancy, this concept has emerged from the observation of a spin-phonon coupling in a variety of rare-earths based materials. The magnetic excitations involved in the magnetoelastic coupling at play in those compounds are not standard magnons, but low energy crystal field excitations (CEF). Since the latter are local electronic excitations, they do not disperse and thus cannot be associated with propagating quasiparticles. In other words, they are not potential heat carriers hence do not contribute to k, in contrast with dispersive magnetic quasiparticles like magnons. However, they can significantly reduce the phonon lifetime by opening a new scattering mechanism.
The aim of the PhD thesis is therefore to investigate, both experimentally and theoretically, magnetoelastic coupling and its impact on thermal conductivity. The systems to be studied will be (but not restricted to) Tb perovskites, and will include high-entropy or entropy stabilized compositions, displaying glass-like thermal conductivity.
In recent years, progress in the field of frustrated magnets have led to the emergence of innovative concepts including new phases of matter. The latter’s do not show any long-range order (no symmetry breaking), but, in classical systems, exhibit a highly degenerate ground state made of classical configurations. An emblematic example is spin ice in pyrochlores : in this case, the construction of those configurations relies on a simple rule, which states that the sum of the four spins in any tetrahedron of the magnetic lattice must be zero. This so-called “ice rule” can be understood as the conservation rule of an emergent gauge field. Experimental evidence of this physics was provided by the observation of singular points in the spin-spin correlation function by elastic neutron scattering experiments. Such singular points, called pinch points, arise because the correlations of the emergent divergence free field are dipolar in nature, with
algebraic spin-spin correlations.
The origin of this physics lies in the conjunction between lattice connectivity, anisotropy and magnetic interactions, which collude to select configurations where a local constraint between spins is preserved. Recently, several authors have proposed a generalization of this concept to other geometries and other constraints, as for instance the “octochlore” lattice, formed by corner sharing octahedra.
Depending on the chosen constraint, different spin liquids have been theoretically predicted.
An experimental realization of the octochlore lattice can be found in rare earth fluorides KRE3F10, as their crystal structure forms a “breathing” network of small and large RE octahedra. Very little is known about the physics of KRE3F10 compounds, apart from magnetization measurements performed two decades ago. The goal of the PhD work will be to characterize the ground state of two Kramers members of the KRE3F10 system (RE = Dy3+, Er3+), to identify in particular any signature of the spin liquid physics suggested by recent theoretical works, and better understand the constraints leading to it.