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

1) 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).

2) Cosmology (data analysis and machine learning): Expertise in inference methods, LSS, cosmological simulations, and CMB are highly valued. The candidate will join the Simons Collaboration in Learning the Universe (https://www.learning-the-universe.org).

3) Machine learning: Representation learning, Bayesian inference, generative modeling, high-dimensional inference, computer vision, graphical models, reinforcement learning. 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. Yoshua Bengio, Prof. Siamak Ravanbakhsh, Prof. Pierre-Luc Bacon, Prof. Julie Hlavacek-Larrondo, and several postdoctoral fellows and graduate students in related research areas. The successful candidates will join Mila, the world’s largest academic research center in deep learning, which rallies 1000 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 physics department including members of iREx, a leading exo-planet Institute.

To express interest, applicants should submit 1) a CV, 2) a detailed publication list and 3) a statement of research through AcademicJobsOnline before June 15, 2023. Applicants should also arrange for three letters of recommendation to be sent through AcademicJobsOnline. Late applications will be considered until the positions are filled.

University of Montreal is committed to diversity and equity within the community. We welcome applications from women, aboriginal persons, persons with disabilities, ethnic minorities, persons of all sexual orientation or gender identity, visible minorities, and others who may contribute to diversification.