We are excited to announce multiple postdoctoral positions in topics related to astrophysics, cosmology, and machine learning in the forthcoming Parsec Institute, affiliated with the University of Montreal. The institute is a major node of the newly funded Simons Collaboration on "Learning the Universe" and also of the FutureLens initiative, funded by the Simons and the Schmidt Futures foundations, respectively. The positions are for 3-year terms, with the possibility of an extension (up to 5 years).

We are seeking candidates who will pursue research in one or more of the following themes:

• Strong gravitational lensing: Experience in lensing data analysis and machine learning is highly valued. The main focus will be cosmology and dark matter science. The candidates will be encouraged to join the FuturesLens initiative and the LSST Dark Energy Science Collaboration (DESC).
• Cosmology (data analysis and machine learning): Expertise in inference methods, LSS, cosmological simulations, and CMB are highly valued. The candidate will join a Simons Collaboration in Learning the Universe (https://www.learning-the-universe.org).
• Black holes: All sciences related to black holes including feedback, emission processes, accretion, and SMBHs in the context of galaxies and galaxy clusters (e.g., ICM cooling, cluster formation and evolution, radio and X-ray observations, etc.). The candidates will be encouraged to collaborate with members of the MWA and SKA collaborations.
• Gaia data analysis: The successful candidate will work in areas related to unsupervised machine learning and anomaly detection with a broad science goal and will work in close collaboration with machine learning experts at Mila.

All candidates are also strongly encouraged to pursue independent research in broader topics related to machine learning and astrophysical data analysis.

The successful candidates will have ample opportunities of exchange with researchers from our partner institutions (Columbia, Berkeley National Lab, Harvard, Flatiron Institute, Stockholm, IAP, Princeton, Carnegie Mellon, MPA Garching, CUNY, Stanford). The candidates will also work in close collaboration with local members, including Prof. Yashar Hezaveh, Prof. Laurence Perreault Levasseur, Prof. Julie Hlavacek-Larrondo, Prof. Siamak Ravanbakhsh, and several postdoctoral fellows and graduate students in related research areas. The successful candidates will be offered the possibility to join Mila, the world's largest academic research center in deep learning, which rallies 500 researchers specializing in this field. We also have strong ties with the Center for Computational Astrophysics at the Flatiron Institute, allowing opportunities for close collaborations with members of this center. The successful candidates will be encouraged to form new collaborations with other members of the department including members of iREx, a leading exo-planet Institute.