The Hoffman Lab at the Princess Margaret Cancer Centre, Toronto, ON seeks postdoctoral fellows to work on research projects in computational genomics and machine learning.
Our lab develops machine learning techniques to better understand chromatin biology. These models and algorithms transform high-dimensional functional genomics data into interpretable patterns and lead to new biological insight. A key focus of the lab is to train a new generation of computational biologists.
We seek postdoctoral fellows for several projects in computational genomics and machine learning. Selected projects include:
- Integrating epigenomic and sequence data to better understand human gene regulation.
- Developing deep learning techniques to find novel behavior in multiple functional genomics datasets.
- Creating models of transcription factor binding that allow us to predict the effects of perturbations.
The Princess Margaret Cancer Centre is a teaching hospital affiliated with the University of Toronto. It has the largest cancer research program in Canada. It is a component of the University Health Network, Canada's largest hospital.
The Hoffman Lab is part of a Centre for Cancer Epigenomics at the Princess Margaret. There are ample opportunities for collaboration and scientific exchange with a large community of genomics, computational biology, and machine learning groups at the University of Toronto and associated institutions.
Required qualifications: Doctorate in computational biology, computer science, electrical engineering, statistics, or physics. Submitted papers in genomics or machine learning research. Expertise in Python and Unix environments.
Preferred qualifications: Experience with epigenomics and graphical models. Published papers in peer-reviewed journals or refereed conference proceedings. Expertise in R, C, and C++.
To apply: We will accept applications until the position is filled. Please submit a CV, a PDF of your best paper, and the names, email addresses, and phone numbers of three references to the address at our recruitment web page.
