Development of photo-printed interferometric biosensors on multi-core optical fibers for molecular diagnostics
Optical fibers are minimally invasive devices commonly used in medicine for in vivo tissue imaging by endoscopy. However, at present, they only provide images and no molecular information about the tissues observed. The proposed thesis is part of a project aimed at giving optical fibers the ability to perform molecular recognition in order to develop innovative biosensors capable of performing real-time, remote, in situ, and multiplexed molecular analysis. Such a tool could lead to significant advances in the medical field, particularly in the study of brain pathologies, where knowledge of the tumor environment, which is difficult to access using conventional biopsies, is essential.
The proposed approach is based on 2-photon polymerization printing of interferometric structures at the end of each core of a multifiber assembly. The detection principle is based on the interference occurring in these structures and their modification by the adsorption of biological molecules. Each fiber in the assembly will act as an individual sensor, and measuring the intensity of the light reflected at the functionalized end will provide information about the biological interactions occurring on that surface. By modeling the interference phenomenon, we determined parameters to optimize the shape and sensitivity of interferometric structures (PTC InSiBio 2024-2025). These results enabled the printing and characterization of the sensitivity of interferometric structures on single-core fibers. The objectives of the thesis are to continue this optical characterization on new samples and to develop original photochemical functionalization methods in order to graft several biological probes onto the surface of the fiber assemblies. This multi-functionalization will enable multiplexed detection, which is essential for future medical applications. Depending on the progress of the thesis, the biosensors will be validated through the detection of biological targets in increasingly complex environments, up to and including a brain tissue model.
Mining LEP data for fragmentation: A TMD-oriented analysis of pi+pi- pairs in e+e- collisions
This project aims to advance our understanding of quark and gluon fragmentation by performing the first-ever extraction of Transverse-Momentum-Dependent Fragmentation Functions (TMDFFs) for charged pions using archived data from LEP experiments like DELPHI or ALEPH.
Fragmentation Functions, which describe how partons form detectable hadrons, are non-perturbative and must be determined from experimental data. TMDFFs provide more detailed information about the transverse momentum of these hadrons. An ideal process to study them is the production of back-to-back pi+pi- pairs in electron-positron annihilations, a measurement surprisingly absent from both past and current experiments.
The project will leverage CERN OpenData initiative to access this historical data. The work is structured in three key steps: first, overcoming the technical challenge of accessing the data using potentially obsolete software; second, extracting relevant physical distributions, such as the transverse momentum of the pion pairs; and third, using Monte Carlo simulations (e.g., Pythia8) to interpret the results.
A crucial part of the analysis will be to identify the observables most sensitive to TMDFFs through simulations. The final data analysis will employ modern techniques to ensure a robust estimate of all uncertainties. Once completed, this pioneering measurement will be incorporated into a global analysis of TMD data, significantly improving the accuracy of TMDFFs and pushing the boundaries of our knowledge of non-perturbative QCD.
Development of the Micromegas CyMBaL Detector and study of gluon saturation for the future electron-ion collider
The future Electron-Ion Collider (EIC), to be constructed at Brookhaven National Laboratory (NY, USA) is a next-generation facility designed to explore the inner structure of protons and nuclei with unprecedented precision. It will explore how quarks and gluons generate the mass, spin, and structure of visible matter, and study the increase of gluon density at small Bjorken-x. To meet its ambitious physics goals, innovative detectors are being developed — including the Micromegas CyMBaL system, a gaseous tracker for the central region of the first EIC experimental apparatus ePIC.
This PhD project combines experimental detector R&D and physics simulations:
* Prototype characterization: build and test full-scale Micromegas detectors; measure efficiency, gain uniformity, and spatial resolution in laboratory and beam environments. Test and validate the prototypes with the new ASIC SALSA developed at CEA for gasesous detectors at ePIC.
* Detector simulations: integrate the CyMBaL geometry into the EIC framework and assess global tracking and performance requirements.
* Physics studies: simulate key processes sensitive to gluon saturation (e.g. final-state di-hadron correlations) to understand QCD at small-x and evaluate how detector performance influences physics sensitivity.
The PhD student will have opportunities to participate in the development of state-of-the-art gaseous detectors and to work within an international community of hadronic physicists on topics at the forefront of the field, with trips to Brookhaven National Laboratory (NY, USA) and opportunities for test-beam campaigns at accelerator facilities.
TRANSFORMER: from the genealogy of dark matter halos to the baryonic properties of galaxy clusters.
The thesis proposes to predict the baryonic properties of galaxy clusters based on the history of dark matter halo formation, using innovative neural networks (Transformers). The work will involve intensive numerical simulations. This project falls within the general framework of determining cosmological parameters through the observation of galaxy clusters in X-rays. It is directly linked to the international Heritage programme in the XMM-Euclid FornaX deep field.
ULTRAFAST SENSING BY ELECTRON AND MAJORANA FLYING QUBITS
An emerging pathway for quantum information is the use of flying electronic charges, such as single-electron excitations, as qubits.
These flying qubits present a key advantage: their intrinsic Coulomb interaction, which enables deterministic two-qubit gates and applications in quantum sensing.
Compared to photonic qubits, they therefore provide a natural means to overcome certain fundamental limitations.
Their main drawback lies in rapid decoherence, but this challenge can be mitigated by operating at ultrafast timescales, on the order of a picosecond.
An additional strategy involves exploiting the topological protection provided by Majorana modes, non-Abelian quasiparticles that are insensitive to local perturbations.
So far, most research has focused on localized 0D modes (at the ends of superconducting nanowires), with no conclusive experimental demonstrations.
This project proposes a new approach based on 1D chiral Majorana modes, offering a pathway toward topologically protected flying qubits.
The ambition is to establish a novel platform for quantum computing and quantum sensing.
This platform will exploit engineered multilayer graphene, combining the quantum anomalous Hall effect, superconductivity, and chiral Majorana modes.
Network structures and development dynamics - from the Industrial Revolution to the Energy Transition
Networks are crucial components of complex societies and underlie successful climate-energy strategies. Nevertheless they remain relatively understudied and insufficiently understood in their dynamics as well as in their relation to resource consumption and economic prosperity.
In this doctoral project, several historical cases of physical network will be explored from an industrial ecology standpoint and in relation to energy consumption. The project will address complexity in sociotechnical network structures and uses based on a complex systems modelling approach associating statistical physics (graph theory), geography and economic history. The project will mainly focus on the transportation and energy networks and their entanglement.
A first target will be railway networks that progressively grew during the 19th century in relation to coal extraction, trade and use. Railway networks are intertwined with early-industrial sociotechnical development and paved the way to the development of road networks in the 20th century in particular on the basis of complex oil networks. The study will address the dual role of railways and road networks in the transportation of both passengers and freight of energy and materials. The growth rates, interconnections and key metrics of these networks will be jointly analyzed and compared to an equivalent analysis of electricity grids which are currently under study by members of the PhD proposal team.
Coupled Friction Effects of Dirac sea and Electromagnetic Vacuum on Atomic movements
Quantum fluctuations induce conservative macroscopic forces such as the Casimir effect. They could also cause dissipative forces, termed vacuum (or quantum) friction. Up to now, this friction effect has been calculated with consideration of the electromagnetic fluctuations only, i.e. without taking into account the Dirac Sea. This project is devoted to the extension of our research in this direction: electrons, as main contributors of the matter-field interaction, also interact with electron-positron virtual pairs in the quantum vacuum. How much of quantum friction, at zero or finite vacuum temperature, could be due to this type of interaction? A first step will be adapting the present semi-classical framework to include vacuum polarization and pair creation. In doing so, one will encounter finite frequency cut-offs, traditionally linked to virtual pair creation; thus one will determine a friction component linked with the finite cut-off of Fourier integrals. On this research path, one shall pay attention to maintaining the mathematical coherence of the whole framework. A longer-term goal remains a complete and consistent quantum relativistic treatment of quantum friction at the atomic level.
Dynamic interplay of Rad51 nucleoprotein filament-associated proteins - Involvement in the regulation of homologous recombination
Homologous recombination (HR) is an important mechanism for the repair of ionizing radiation- induced DNA double-strand breaks. A key step in HR is the formation of Rad51 nucleoprotein filaments on the single-stranded DNA that is generated from these breaks. We were the first to show, using yeast as a model, that a tight control of the formation of these filaments is essential for HR not to induce chromosomal rearrangements by itself (eLife 2018, Cells 2021, Nat. Commun. 2025). In humans, the functional homologs of the yeast control proteins are tumor suppressors. Thus, the control of HR seems to be as important as the mechanism of HR itself. Our project involves the use of new molecular tools that allow a breakthrough in the study of these controls. We will use a functional fluorescent version of the Rad51 protein, developed for the first time by our collaborators A. Taddei (Institut Curie), R. Guérois and F. Ochsenbein (I2BC, Joliot, CEA). This major advance will allow us to observe the influence of regulatory proteins on DNA repair by microscopy in living cells. We have also developed highly accurate structural models of control protein complexes associated with Rad51 filaments. We will adopt a multidisciplinary approach based on genetics, molecular biology, biochemistry, and protein structure to understand the function of the regulators of Rad51 filament formation. The description of the organization of these proteins with Rad51 filaments will allow us to develop new therapeutic approaches.
Machine Learning-Based Algorithms for Real-Time Standalone Tracking in the Upstream Pixel Detector at LHCb
This PhD aims to develop and optimize next-generation track reconstruction capabilities for the LHCb experiment at the Large Hadron Collider (LHC) through the exploration of advanced machine learning (ML) algorithms. The newly installed Upstream Pixel (UP) detector, located upstream of the LHCb magnet, will play a crucial role from Run 5 onward by rapidly identifying track candidates and reducing fake tracks at the earliest stages of reconstruction, particularly in high-occupancy environments.
Achieving fast and highly efficient tracking is essential to fulfill LHCb’s rich physics program, which spans rare decays, CP-violation studies in the Standard Model, and the characterization of the quark–gluon plasma in nucleus–nucleus collisions. However, the increasing event rates and data complexity expected for future data-taking phases will impose major constraints on current tracking algorithms, especially in heavy-ion collisions where thousands of charged particles may be produced per event.
In this context, we will investigate modern ML-based approaches for standalone tracking in the UP detector. Successful applications in the LHCb VELO tracking system already demonstrate the potential of such methods. In particular, Graph Neural Networks (GNNs) are a promising solution for exploiting the geometric correlations between detector hits, allowing for improved tracking efficiency and fake-rate suppression, while maintaining scalability at high multiplicity.
The PhD program will first focus on the development of a realistic GEANT4 simulation of the UP detector to generate ML-suitable datasets and study detector performance. The next phase will consist in designing, training, and benchmarking advanced ML algorithms for standalone tracking, followed by their optimization for real-time GPU-based execution within the Allen trigger and reconstruction framework. The most efficient solutions will be integrated and validated inside the official LHCb software stack, ensuring compatibility with existing data pipelines and direct applicability to Run-5 operation.
Overall, the thesis will provide a major contribution to the real-time reconstruction performance of LHCb, preparing the experiment for the challenges of future high-luminosity and heavy-ion running.
Influence of a nano-antenna on the intersystem crossing rate of a single molecule
As part of the continuation of the ANR JCJC PlasmonISC project, we propose a thesis subject mainly experimental in nano-photonics. The objective of the thesis is to study the influence of a nano-antenna (plasmonic, magnetic or dielectric) on the rate governing the photophysics of fluorescence emission from a single molecule, with a particular interest in the intersystem crossing rate. We have developed a dedicated optical bench combining optical and atomic force microscopy, an experimental procedure, as well as signal processing tools, showing encouraging first results with a dielectric tip. We wish to continue to explore the single molecule/nano-antenna interaction with other types of tips generating other physical effects. The ability to control the transition to the triplet state is of great interest for single photon sources, organic light emitting diodes, and in chemistry.