Postdoctoral Researcher (M/F)

Job Description

Missions

The successful candidate will carry out postdoctoral research within the LPENS astrophysics team, as part of the ANR ForeSight project, which develops innovative approaches to separating the primordial B-modes of the cosmic microwave background from polarized Galactic microwave foregrounds. The precise research topic will be defined jointly with the team at the start of the contract, depending on the candidate's skills and interests and the progress of the project.Two main axes structure the project and will serve as a starting point for defining the topic: (i) extending ST-based component separation to multi-frequency, multi-component configurations, in connection with the application to detecting primordial CMB B-modes; (ii) positioning these methods relative to classical component-separation approaches, both through validation and hybridization with these approaches, and through the development of new ST algorithms built from scratch where existing methods fall short.

Activity

Contribute to the development of non-Gaussian component-separation algorithms based on Scattering Transforms, in particular in multi-frequency configurations (extending the framework developed in Tsouros et al. 2026).
Study how ST methods relate to classical component-separation approaches (GNILC, SMICA, NILC, Commander, parametric approaches): comparison, cross-validation, and hybridization where relevant.
Design and implement new ST algorithms not covered by existing approaches, as needed by the project.
Contribute to applying these methods to real data (Planck, and eventually Simons Observatory / LiteBIRD) on polarized Galactic foregrounds (dust, potentially synchrotron).
Use and contribute to the STL Python library, the team's shared software foundation for Scattering Transform computations.
Take part in the team's scientific meetings (weekly meetings, Scattering Club seminar) and in exchanges with project collaborators.
Work closely with other team members on related topics (component separation, Bayesian inference in ST space, software development).
Regularly present progress within the group and at external conferences or seminars, and disseminate results through publications in peer-reviewed journals.

Your Profil

Skills

PhD in astrophysics, physics, data science, statistics, or signal processing.
Solid research experience in at least one of the following areas: cosmology/CMB, interstellar medium physics, statistics and inference, signal processing, or machine learning applied to physical sciences.
Good command of Python and associated scientific libraries (NumPy, PyTorch or equivalent); familiarity with Scattering Transforms is a plus but not required — hands-on onboarding will be provided.
Interest in working at the interface between astrophysics and data science, and ability to quickly get up to speed with methods and tools outside one's initial area of specialization.
Scientific autonomy, rigor, and ability to contribute to defining one's own research project within a collective framework.
Enjoyment of collaborative work within a multidisciplinary team.
Good written and oral communication skills, in French and/or English.

Your Work Environment

The position is based at the Laboratoire de Physique de l'École normale supérieure (LPENS), within the astrophysics team, with a possible affiliation to the ENS-PSL Center for Data Science. The working environment is interdisciplinary, at the interface between astrophysics, applied mathematics, and data science.
The ANR ForeSight project (2025–2029) aims to build generative models of polarized Galactic foregrounds directly from observational data, building on Scattering Transforms, with a view to their application to detecting primordial CMB B-modes. The successful candidate will join an already established team (several PhD students and postdocs, with recent work on polarization component separation and on Bayesian inference in ST statistics space), and will benefit from the existing software infrastructure (STL library) and computing resources (the team's GPU cluster, access to national facilities such as IDRIS) already in place.

Constraints and risks

No particular constraints or conditions. Work on a standard computer workstation, with access to local GPU computing resources and national computing facilities.

Compensation and benefits

Compensation

Between €3,500 and €4,800 gross per month, depending on experience

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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