The François group is looking for outstanding post-doctoral candidates. Candidates should have a Ph.D. in theoretical or computational physics/biophysics/computer science, or in a related field, and a very strong interest in biology. Experience in machine learning techniques (in a very broad sense) is a plus. Candidates with a background in theoretical or numerical approaches to complex systems are also encouraged to apply. Candidates should have obtained their Ph.D. within the last 2 years.

We are especially looking for candidates combining theoretical and computational approaches (including machine learning) to understand fundamental aspects of biology. Examples of  topics studied in the group include:

-        Immune recognition, following up on our recently published work on Universal Antigen Encoding (Achar et al, Science, 2022), within our collaboration with the group of Grégoire Altan-Bonnet at the National Cancer Institute (USA)

-       Embryonic development, following our long-term collaboration with the group of Alexander Aulehla at EMBL (Germany)

-       Evolutionary algorithms, following our works on in silico evolution and machine learning.

More information on the current research directions in the group is available on the Francois Research Group website. The positions will be funded by Fonds Courtois, NSERC, and CIHR, and are renewable based on performance.

The candidates will be part of a vibrant research ecosystem, with multiple collaborations, within Montréal (Université de Montréal and McGill) and with multiple international groups. The positions will be based at Université de Montréal, one of the most prestigious Research Universities in Canada. The candidate will be part of the Biophysics/Bioinformatics subgroup in the Biochemistry and Molecular Medicine Department,  which is part of the newly launched Centre d’Initiative Biomédicale. The Candidate will also be an Associate post-doc to MILA Québec, the Québec Machine Learning Research Institute, home to more than 1000 researchers specialized in machine learning and dedicated to scientific excellence and innovation.

Montréal is often described as Canada’s cultural capital, is multicultural and multilingual, and is regularly ranked as one of the top cities in North America to study.  We are committed to Equity, Diversity and Inclusion. We adopt a broad and inclusive definition of diversity that goes beyond applicable laws, and we encourage all qualified individuals, regardless of their characteristics, to apply.

Please send applications, including CV, a couple of representative publications, a short statement, and reference names to Paul François.