Université de Montréal, Département de mathématiques et de statistique

Position ID: UdeM-POSTDOC1 [#21433]
Position Title: Postdoc positions in machine learning and data science
Position Type: Postdoctoral
Position Location: Montréal, Quebec H3C 3J7, Canada [map] sort by distance
Subject Area: Machine learning and data science
Application Deadline: 2022/12/15 11:59PMhelp popup (posted 2022/11/04, listed until 2023/05/04)
Position Description:    

Postdoc positions in machine learning and data science

 The RAFALES research group of Professor Guy Wolf at the Dept of Math & Stat (DMS) at Université de Montréal (UdeM) expects to have two postdoctoral fellow positions available starting in the spring of 2023. The research conducted in this group, at the intersection of UdeM, Mila (the Quebec AI institute) and CRCHUM (the Montreal university hospital research center), spans over a wide range of exploratory data analysis tasks, leveraging tools from manifold learning, graph signal processing, geometric deep learning, and harmonic analysis, to name a few, and is often motivated by real-world data intensive applications.

 The following two positions are expected:

 A. Postdocotal fellow in the intersection of AI and nanophotonic component design, who will have the opportunity to work in collaboration with the researchers Dr. Yuri Grinberg and Dr. Dan-Xia Xu from the National Research Council of Canada. This collaboration is aimed to produce novel deep generative models for efficient optimization and design of nanophotonic components or devices, leveraging advanced neural network architectures together with domain specific understanding of underlying physics, while taking into account aspects of manufacturing feasibility, robustness, and miniaturization.

 Candidate qualifications:

-        Necessary qualification: PhD in electrical engineering, applied math, physics, computer science, or related disciplines.

-        Necessary qualification: Interest in applying machine learning to problems in nanophotonics design.

-        Desired qualification: Experience in applying machine learning to open scientific problems (e.g., from physics, chemistry, or biology).

-        Desired qualification: Demonstrated ability to derive signal processing or machine learning methods from domain-specific considerations.

 B. Postdocotal fellow in the intersection of geometric deep learning, drug discovery, and biomedical data analysis, who will have the opportunity to work in collaboration with several groups from Mila (the Quebec AI institute) and Helmholtz Zentrum in Munich, Germany. This collaboration is aimed to produce novel geometric (graph and manifold) representation learning methods for modeling physiological and immunological processes, as well as drug interactions. These are expected to be leverage in drug discovery applications via deep generative models for efficient in silico identification of drug candidates to be evaluated in vitro via industry collaborations facilitated by Mila.

 Candidate qualifications:

-        Necessary qualification: PhD in applied mathematics, computer science, computational biology and bioinformatics, or related disciplines.

-        Necessary qualification: Interest in applying machine learning to biomedical data analysis applications.

-        Desired qualification: Experience in applying machine learning in to biomedical applications, with emphasis on omic data analysis and drug discovery

-        Desired qualification: Demonstrated ability to derive graph neural networks, graph signal processing or manifold learning methods on real-world data, with emphasis on biology, chemistry, and biomedical data.

Candidates are encouraged to apply via the instructions below.

 Terms and conditions:

 Selected candidates will be primarily affiliated with the DMS at UdeM, and will be considered core postdocs at Mila. The position is intended for a total duration of two years, in the form of a limited-term contract for one year, renewable to a second year subject to performance and continuity of available funding. Postdoctoral fellows at the Université de Montréal are protected by their collective bargaining agreement. Specifically, postdoctoral fellows are entitled to accumulate vacation at a rate of 2 days per month, up to a maximum of 23 working days, and are eligible for health coverage from the Régie de l’assurance maladie de Québec. International postdoctoral fellows are exempt from provincial taxes.

 Application instructions:

 To apply, please submit the following materials via mathjobs

-        Cover letter specifying which of the positions is of interest to the candidate

-        Résumé/CV and list of publications

-        Research statement

-        Two or three letters of recommendation, including one from the PhD advisor.

 Review of applications will begin in December and continue until the position is filled. Full consideration will be given to candidates who apply before December 15, 2022.


Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
www.dms.umontreal.ca
+1 514 343 6694
 
Département de mathématiques et de statistique
Faculté des arts et des sciences
C.P. 6128, Succursale Centre-Ville
Montréal, QC
H3C 3J7