Research overview Materials can be studied using computer simulation which enables one to probe the motion of each constituent atoms and to build correlations between the macroscopic properties and the microscopic behaviors. On the one hand, traditional quantum mechanics methods provides particularly accurate results up to the electronic structure of the material. Yet, the drawback of this method concerns its computational cost which prevents from studying large system sizes and long time scales. On the other hand, effective potentials have been developed to mimic atomic interactions thereby reducing those issues. However, these potentials are often built to reproduce bulk properties of the materials and can hardly be employed to study some specific systems including interfaces and nanomaterials. In this context, a new class of interatomic potentials based on machine-learning algorithms is being developed to retain the accuracy of traditional quantum mechanics methods while being able to run simulations with larger system sizes and longer time scales. Simulation project Using computer simulations, the student will construct a database that should be representative of the different interactions occurring in a specific material. Machine-learning potentials based on the least-angle regression algorithm as well as neural network potentials will be trained and their accuracy will be studied as a function of the size and the complexity of the database.

Research overview The formation of a crystal is triggered by the emergence of a nucleation core. Classical nucleation theory (CNT) is widely employed to discuss its nature and its origin. In CNT, the thermodynamically stable phase is always the one that grows first and its size is then driven by the free energy competition between how much it costs to build a liquid-crystal interface and the gain from growing the crystal. Yet, following Ostwald’s rule, another structure may emerge beforehand if it is closer in free energy to the mother phase. Then, structural and also chemical reorganizations happen during the growth. This multi-stage nucleation mechanism already appears in bulk systems but can be amplified in nanocrystal nucleation where surface effects and chemical reactivity are enhanced. For nanoscience to be inspired by the practical applications instead of still being driven by the synthesis possibilities, it is crucial to reach a better understanding of the unique crystallization mechanisms leading to nanocrystals. Simulation project Atomistic simulations will be performed to study crystallization of binary particles. Examples will be taken from well-studied materials including CuZr, NiAl, NaCl, Water... We will investigate the correlation between the thermodynamic conditions and the final nanoparticles. The goal is to ultimately better understand how nucleation theory is affected by downsizing to the nanometric scale.

It is not really understood how a plant can recover after the development of an air embolism after the nucleation of cavitation bubbles in their hydraulic network, some studies calling for a "miracle". An emerging hypothesis focuses on solutes (salts, sugars) to trigger the nucleation and growth of new droplets, which will refill the dry parts of the hydraulic circuit. The main objective of the internship is to understand the physics of the refilling when solutes are present. Our approach will be to manufacture biomimetic leaves made of a thin layer of transparent silicone.

The project focuses on mixtures of electrons (fermion) and excitons (electron-hole pair, a boson) in a new class of materials: van der Waals heterostructures. The latter can be seen as a “mille-feuille”, obtained by stacking atomically thin sheets of various materials. They recently became a prominent platform to study many-body physics, after a milestone discovery of superconductivity in bilayer graphene. Our long term ambition is to introduce superconductivity in a controlled manner, using excitons as force-carrier bosons (instead of phonons in conventional superconductors). The internship will pave the way toward this goal. It includes two steps, (i) the fabrication of the heterostructures and (ii) a first characterization with optical spectroscopy.

Our project tackles the fundamental challenge of bridging the diverse temporal and spatial scales of biological development. From the nanoscale molecular interactions that occur in seconds to the formation of millimeter-to-meter-scale tissues over days, nature's complexity is staggering. This project seeks to unveil how information flows from molecular transcription factors to orchestrate tissue formation. This project employs a multidisciplinary approach, combining experimental techniques (quantitative microscopy) with theoretical modeling (polymer and statistical physics). It aims to decode the mechanisms governing the interplay between cellular regulation and tissue development. This research has broad implications for biophysics, developmental biology, and regenerative medicine.

This research project aims to uncover the biophysical principles that enable mammalian embryonic stem cells to self-organize into synthetic organoid structures reminiscent of mouse embryos. Our approach blends mathematical modeling with precise single-cell measurements to investigate the emergence of positional and correlative information within differentiating stem-cell aggregates. By integrating theoretical predictions with experimental data, the project will compare dynamic information flow across various developmental systems, such as fly embryos and stem-cell-derived organoids. This interdisciplinary effort not only bridges quantitative and life sciences but also offers students a collaborative environment where they can take ownership of their research and help define the project’s direction.

Can the motion of animal collectives be described as the flows of soft active matter? To answer this question, we combine field studies of massive fish schools, extensive data analysis, machine learning, and mathematical modelling. Depending on your interests and the scope of your internship, you will contribute to a selection of these efforts. Reach out to learn more about our research!