Postdoctoral position in differentiable modelling and cosmological inference for Rubin/LSST (M/F)

Job Description

Missions

To contribute to the AstroDeep project, jointly led by the APC (Université Paris Cité/CNRS) and CosmoStat at CEA Paris-Saclay, with a view to developing cosmological inference methods based on forward modelling for the analysis of the LSST survey from the Vera C. Rubin Observatory.
To exploit the cosmological information contained in the non-linear structure of matter fields and weak gravitational shear, beyond traditional statistics, by linking cosmological parameters to observables via physical models and automatically differentiable simulations.

Activity

To develop and validate differentiable cosmological models for the evolution of large-scale structures and gravitational shear observables, whilst assessing their accuracy and performance.
To develop inference methods that utilise these models and their gradients, to characterise biases and uncertainties, and to study scaling, the marginalisation of nuisance parameters and robustness to systematic effects.
Apply the workflow to realistic simulations and data from precursor surveys such as DES, then prepare for and, subject to data availability, carry out the cosmological analysis of LSST Y1 within the LSST DESC collaboration.
Integrate the tools into the LSST pipelines and validate them on volumes representative of the survey; document and distribute the open-source code, and disseminate the results through scientific publications and presentations.

Your Profil

Skills

PhD, or due to defend shortly, in astrophysics, cosmology, physics, statistics or a related field.
A good command of at least one of the following areas: cosmological simulations, large-scale structure evolution, weak gravitational shear, differentiable modelling, Bayesian inference or gradient-based inference methods.
Experience with automatic differentiation frameworks such as JAX or PyTorch would be an advantage, as would experience with tools for cosmological simulation, Bayesian sampling or high-performance computing.
Strong skills in Python programming and collaborative development (Git/GitHub, CI/CD, open-source practices).
Ability to conduct research independently whilst contributing effectively to an interdisciplinary team.
Excellent scientific communication skills in English, both written and spoken. Experience in cosmological data analysis or in large astronomical collaborations, such as DES or the LSST DESC, is an asset but not essential.

Your Work Environment

The AstroDeep project aims to harness the full informational content of large Phase IV imaging surveys by developing a unified, probabilistic and differentiable framework for cosmological analysis.
A two-year postdoctoral position is available at the APC in Paris, starting in early December 2026, within a dynamic research environment at the interface between cosmology, statistics and data science.
The AstroDeep team at the APC is based in the heart of Paris and is heavily involved in international collaborations such as Euclid and the LSST DESC.
The project and the laboratory promote a collaborative, inclusive and work-life-balance-friendly working environment, with benefits such as comprehensive health cover, holiday entitlement, subsidised meals, transport discounts and optional French language courses.

Constraints and risks

No particular risks.
Travel within France or abroad is to be expected.

Compensation and benefits

Compensation

Between €3,132.83 and €4,343.20 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

The research professions