Position Title: Postdoctoral Researcher in Machine Learning / Statistical Learning
Laboratory: Laboratoire des Signaux et Systèmes (L2S), CNRS – CentraleSupelec – Université Paris-Saclay, Gif-sur-Yvette, France
Contract Duration: 12 months (can be longer, depending on funding availability and progress)
Start Date: From 01-Jun-2025 to 01-Nov-2025
Application Deadline: 24-Mar-2025
About L2S
The Laboratoire des Signaux et Systèmes (L2S) is a joint research unit of the French National Centre for Scientific Research (CNRS), CentraleSupélec, and Université Paris-Saclay. L2S conducts fundamental and applied research in signal and image processing, control theory, information theory, and communications. The “Signals and Statistics” research group at L2S focuses on developing advanced methods for data analysis, statistical learning, signal and image processing, and inverse problems, with applications in various fields such as health, non-destructive testing, acoustics, remote sensing, and astrophysics. More information can be found at https://l2s.centralesupelec.fr/.
Project Description
This postdoctoral position is part of a selective program specifically designed to prepare outstanding candidates for permanent researcher applications. The successful candidate will conduct research in machine learning and statistical learning, with a focus on applications within one or more of the following areas of expertise at L2S:
- Inverse Problems and Computational Imaging: Developing advanced machine learning techniques for solving inverse problems arising in imaging applications.
- Robust Statistics: Designing robust statistical methods to handle noisy and corrupted data in signal and image processing.
- Health and Environment: Applying machine learning and statistical learning to address challenges in health (e.g., medical imaging, bioinformatics) and environment (e.g., environmental monitoring, climate modeling).
- Uncertainty Quantification: Developing methods for quantifying uncertainty in machine learning models and their predictions, with applications to the aforementioned areas.
The research will involve the development of novel algorithms, theoretical analysis, and numerical simulations. The candidate will have the opportunity to collaborate with leading researchers at L2S and participate in national and international conferences. A strong emphasis will be placed on publishing high-impact research papers in top-tier journals and conferences.
Candidate Profile
- PhD in Machine Learning, Statistics, Applied Mathematics, Computer Science, Electrical Engineering, or a related field.
- Strong background in machine learning and statistical learning theory and methods.
- Experience in one or more of the following areas is highly desirable: inverse problems, computational imaging, robust statistics, uncertainty quantification.
- Good programming skills (e.g., Python, MATLAB).
- Strong mathematical and analytical skills.
- Excellent communication and writing skills in English.
- Demonstrated ability to conduct independent research and work collaboratively in a team.
- A strong motivation to pursue an academic research career is essential.
What We Offer
- A stimulating and international research environment at a leading research institution within the vibrant Paris-Saclay University campus.
- Mentorship and guidance from experienced researchers to prepare for academic researcher applications.
- Access to state-of-the-art computing resources.
- Opportunities to collaborate with national and international partners, within the extensive Paris-Saclay ecosystem and beyond.
- Salary and benefits according to CNRS standards.
Application Procedure
Interested candidates are invited to submit the following documents in PDF format to charles.soussen@l2s.centralesupelec.fr and francois.orieux@universite-paris-saclay.fr:
- A detailed CV including a list of publications.
- A cover letter outlining their research interests, relevant experience, and motivation for applying to this position.
- A research statement describing their past research contributions and future research plans (maximum 2 pages).
- Two letters of recommendation (sent directly by the referees).
Selection Process
Applications will be reviewed by a selection committee composed of L2S researchers. Shortlisted candidates will be invited for an interview (in person or via video conference). The selection process is competitive, with a focus on identifying candidates with the highest potential for a research career.
Contacts
- Charles Soussen, head of “Signals and Statistics” research group – charles.soussen@centralesupelec.fr
- François Orieux – francois.orieux@universite-paris-saclay.fr
Equal Opportunity Employer
L2S is an equal opportunity employer and encourages applications from all qualified candidates regardless of gender, race, ethnicity, religion, or disability.
