Academic background & Professional Experiences
Summary
I am Jules Perret, a PhD researcher and research engineer in gravitational astrophysics at the Astroparticle and Cosmology Laboratory (APC, CNRS). My work focuses on data analysis for the LISA space mission, combining Bayesian inference and advanced computational methods to extract astrophysical insights from gravitational-wave signals.
I am particularly interested in numerical simulations applied to astrophysics. With my Master’s degree from École Normale Supérieure Paris-Saclay - Université Paris-Saclay, I developed a strong interest in High-Performance Computing (HPC) and massive parallel development on CPU/GPU.
Education
PhD in Astrophysics
- Institution: Laboratoire Astroparticule et Cosmologie APC-CNRS
- Duration: 2022 - Present
- Description:
- Development of Python package: Deep Hamiltonian Monte Carlo (DeepHMC) for parameter estimation of gravitational wave sources.git
- Bayesian statistics and numerical applications.
- Member of the Ligo-Virgo-Kagra (LVK) Collaboration.
Master’s Degree in High Performance Computing & Numerical Simulation
- Institution: Ecole Normale Supérieure Paris-Saclay, Paris, FR
- Duration: 2020 - 2022
- Description:
- Multiscale computing and domain decomposition method
- Simulation and modeling in fluid mechanics
- Classical mechanics
- Linear algebra for very large problems
- Programming for GPU architecture and supercomputing
Bachelor’s in Computer Science & Full Stack Web Development
- Institution: Université de Bourgogne
- Duration: 2016 - 2020
- Description:
- Database (Oracle, SQL, PostgreSQL)
- Web development (PHP, HTML5/CSS, JavaScript, AJAX)
- Software engineering, graphic interface (JavaFX, MVC model)
- Using a GNU/Linux environment
- Java, C, C++, assembler programming
- Multithreading and networking
- Image analysis (Matlab, OpenCV)
- Image synthesis and Ray-Tracing technologies
Preparatory Year / 1st Year Bachelor in Physics
- Institution: Université de Montréal
- Duration: 2014 - 2016
- Description:
- Linear algebra, analysis, integral calculus
- Classical mechanics, electromagnetics, and astrophysics
- Numerical physics, numerical modeling of physical phenomena, particle interaction
- Environmental chemistry
Professional Experience
PhD in Gravitational Wave Physics & Data Analysis
- Institution: Laboratoire Astroparticule & Cosmologie, Paris, CNRS, FR
- Duration: 2022 - Present
- Responsibilities:
- Devellopment of Deep Hamiltonian Monte-Carlo (DeepHMC) for Parameter Estimation (PE) of gravitaionnal waves data.
- Bayesian statistics
- General relativity and simulation
- Python devellopment using PE LVK’s collaboration package : Bilby
- Simulation of Gravitationnal waves detection and analysis for the third generation of Graviationnal waves detector: Einstein Telescope.
Intern at Lawrence Berkeley National Laboratory (UC BERKELEY - LBNL )
- Position: Astrophysics Internship
- Location: Berkeley, CA, USA
- Duration: 2017 - 2018
- Responsibilities:
- Modelisation of Continious Gravitationnal Waves from pulsar.
- Data Analysis of data from the LIGO and VIRGO detectors.
- Development of parallel FFT algorithms on GPU.
- Python, C/C++ programming
Intern in Software Development (Université de Bourgogne )
- Position: IT Internship
- Location: Dijon, France
- Duration: 2017 - 2018
- Responsibilities:
- Development of mixed reality applications for the Microsoft Hololens platform
- design, develop and test an application using : C#, Unity, Microsoft, MRTK.
- Using 3Dslicer to process tomography of brain image data.