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| PhD position on radiative-transfer modelling of strongly-lensed supernovae in Marseille, France | Closing date: 2026-03-13
Contact: Stéphane Blondin |
We are looking for a highly-motivated PhD student as part of the recently-awarded international French-German grant "SuperEarly: Constraining Supernova Progenitors through Strong Lensing in the Rubin LSST Era", and whose main task will be to carry out radiative-transfer modelling of supernovae, to compare the predicted light curves and spectra with actual observations of lensed SNe to be discovered by Rubin/LSST.
Starting date: September 2026
Duration: 3 years (fully funded)
Salary: 2300 EUR / month (gross) + employee benefits
Application deadline: 13th March 2026 | | ▸ more | A strongly lensed SN offers a unique opportunity to access the first hours/days of its evolution, providing key information on the progenitor and explosion mechanism. The upcoming Vera Rubin Observatory will discover more than 100 lensed SNe of all types during its ten-year Legacy Survey of Space and Time (LSST). Our three-year project will allow us to obtain the earliest rest-frame UV observations of SNe ever made. Our complementary expertise in deep-learning classification, lens and SN modelling, combined with our access to LSST data and follow-up facilities, will yield unprecedented constraints on the progenitors of all types of SNe shortly after they explode.
Our project is inherently interdisciplinary as it relies on the combination of machine-learning algorithms, astronomical observations, and numerical simulations, to reach our targeted goal of constraining supernova progenitors. These various tasks will be distributed among the French and German partners. The PhD student at LAM will focus on radiative-transfer modelling of supernovae. We will compute synthetic spectra and light curves of various supernova types at early times, to compare with the observations of lensed SNe to be discovered by Rubin/LSST. We will use the radiative-transfer code CMFGEN to post-process previously published explosion models, e.g., such as those available for SNe Ia on the HESMA archive (https://hesma.h-its.org). We will also carry out an extensive exploration of the predicted observable properties of existing radiative-transfer simulations computed by our group and available on the Zenodo repository (https://zenodo.org/communities/snrt/).
Our proposed project builds upon the results from the HOLISMOKES program (http://www.holismokes.org/) that was funded by the European Research Council until May 2024. The PI of that program, Sherry Suyu (TUM/MPA), is also part of the project team. At LAM, in addition to the supervisor J.-C. Bouret, the PhD student will also work closely with postdoc Raoul Cañameras (expert on deep-learning algorithms to search for lensed supernovae) and an additional postdoc to be recruited for this project. There will be regular collaboration visits (twice per year) to our German collaborators on the Garching campus near Munich, Germany. There would also be a possibility for the student to spend part of their PhD (up to 1-2 years, TBD) at the European Southern Observatory (ESO) on the same campus, where the co-supervisor S. Blondin is also located. The PhD student will benefit from full data access rights to the Rubin/LSST project.
Keywords: Supernovae - Gravitational lensing - Radiative transfer - Deep learning - Transient surveys
Application details:
Applications should include:
- CV + cover letter
- Copies of diplomas
- Transcripts and ranking in Master's degree
Applications should be sent in PDF format to jean-claude.bouret @ lam.fr and stephane.blondin @ lam.fr by 13th March 2026. Interviews of shortlisted candidates will take place shortly thereafter.
Two letters of recommendation (internship supervisor, Master Program Director, etc.) should also be sent to the same email addresses by the application deadline.
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