- 2023 (5 months)
Graduate Trainee in Cosmology
Institut d'Astrophysique de Paris, France
- Trainee in the "Large-scale structure and distant Universe" group.
- I work with the Aquila Consortium on novel simulation-based inference techniques to extract cosmological information from astronomical data, with future application to Euclid data.
- 2022 - 2023 (1 year)
Master thesis in Fluid Dynamics
ONERA - The French Aerospace Lab, Châtillon, France
- Trainee in the NFLU (Digital methods for fluid dynamics) and MSAT (Advanced turbulence modelling and simulation) teams.
- I developed a novel confinement method to better preserve vortical structures in direct numerical simulations of turbulent flows.
Master's degree in Mathematics and Hybrid AI
Université de Toulouse, France
- Double Master's degree in Mathematics and Hybrid AI, with a strong emphasis on mathematical modelling.
- Prepared at INSA Toulouse and ENSEEIHT (details below).
- 2021 (2 months)
CRG - Centro de Regulación Genómica, Barcelona, Spain
- Summer traineeship in Guigo's Lab.
- I implemented a scalable pipeline for automatic identification of IR-QTL (Intron Retention Quantitative Trait Loci) based on SVA (Surrogate Variable Analysis).
- 2020 - 2022
Junior Bioinformatics Scientist
INSERM (French National Institute of Health and Medical Research), Toulouse, France
- I studied machine learning methods to predict enhancer-gene relations in the human genome ; in parallel to my Master in Mathematical Modelling.
- 2020 (2 months)
IMT (Toulouse Mathematics Institute)
- I studied the convergence speed of series of quantum non-demolition measurements (QND measurements).
- 2020 (4 months)
IRAP - Institut de Recherche en Astrophysique et Planétologie, Toulouse, France
- I studied kinetic scale plasma turbulence in the solar wind.
- 2019 (3 months)
Artificial Intelligence Trainee
Inria (French National Institute for Research in Computer Science and Automation), MIMESIS team
- I analysed the robustness of a deep learning method for data-driven bio-mechanical simulation, with respect to data sparsity and noises.
- As a result, we implemented an efficient transfer learning solution to learn new parameters with few data.
- july 2017
La Ferme aux 100 Blés, Saint-Broing-Les-Moines, France
MS in Mathematical Modelling
INSA Toulouse, France
- Double Master's degree in Mathematics and Hybrid AI with ENSEEIHT
- This is a transversal curriculum built around 3 major axes
- numerical mathematical modelling
- statistical mathematical modelling
- artificial intelligence
MS in Artificial Intelligence
- Double Master's degree (Diplôme d’ingénieur - Master of Science in French Grande Ecoles) in Mathematics and Hybrid AI together with INSA Toulouse.
BS in Fundamental Physics and Internship in Plasma Physics
Paris-Saclay University, Gif-sur-Yvette, France
- I took a full year-off with respect to my training at INSA Toulouse, in order to develop my knowledge of fundamental physics.
- I was enrolled in the Magistère de Physique Fondamentale d’Orsay, where I studied for one semester, and then completed my gap year with 2 traineeships in theoretical physics.
BS in Mathematics and Basic Sciences
INSA Toulouse, France
- 3-year preparatory cycle (Bachelor's degree) in Fundamental and Applied sciences, with a strong emphasis on mathematics. Those 3 years are part of a selective 5-year curriculum leading to a Diplôme d’ingénieur (Master of Science in French Grande Ecoles).
- Scholarship holder (level 6/7)
High School Diploma in Science (Baccalauréat Général Scientifique)
Lycée Charles-Emiles Freppel, Obernai, France
- With highest honors (18.1/20)
- 2022-early 2023
Development of a novel confinement method to better preserve vorticity in direct numerical simulations of turbulent flows
- More to come...
Genome-wide identification of E/G interactions
- If the identification of all enhancers present in a given cell type is not a solved problem, the identification of the relationships between enhancers and genes, i.e. which genes are the targets of which enhancers, in a particular cell type is even more complex. In this project, we investigate two of the most recent methods in the field.
- optimization, optimal control theory, data assimilation, differential equations
- Bayesian and simulation-based inference, physics-informed neural networks, etc
- Simulation for astrophysics, plasma physics, fluid dynamics, etc
- Hobbies: Photography, martial arts, running, hiking, bouldering