Postdoctoral fellowship in computational biology and machine learning

Job type: 
Postdoctoral Fellow
Institution/Company: 
Princess Margaret Cancer Centre
Date Posted: 
Wednesday, December 21, 2016

We seek postdoctoral fellows for several projects in computational genomics and machine learning. Selected projects include:

  1. Integrating epigenomic and sequence data to better understand human gene regulation.
  2. Creating models of transcription factor binding that allow us to predict the effects of perturbations.
  3. Developing deep learning techniques to find novel behavior in multiple functional genomics datasets.

Required qualifications: Doctorate in computational biology, computer science, electrical engineering, statistics, or physics, obtained within the last five years. Submitted first-author or joint first-author papers in genomics or machine learning research. Experience in scientific programming in a Unix environment.

Not required, but preferred qualifications: Experience with epigenomics and graphical models. First-author papers published in peer-reviewed journals, refereed conference proceedings, or a preprint archive. Experience programming in Python, R, C, and C++.

Benefits: Includes extended medical insurance, dental insurance, maternity benefits (15 weeks), parental benefits (additional 35 weeks), child care program (fee applies), defined-benefit pension plan, and employment insurance. Flexible work hours.

https://www.pmgenomics.ca/hoffmanlab/join/#postdoc

Contact Info: 

To apply: We will accept applications until the positions are filled. Please submit your CV (as PDF), one representative paper (as PDF), the URL of a code sample, and the names, email addresses, and phone numbers of three references to join@hoffmanlab.org.

Position open until filled