Goldenberg Lab

University of British Columbia and University of Toronto

We are looking for a motivated postdoctoral fellow with a background in machine learning and computational biology, with an interest in genetics and genomics of psychiatric disorders. The postdoctoral fellow will lead an innovative project on jointly modeling extensive longitudinal psychiatric clinical data and genotypic and genomics data, in order to identify molecular markers of divergent clinical trajectories in psychiatric traits

This project is a collaboration between the University of British Columbia (PI: Sara Mostafavi), and University of Toronto (PI: Anna Goldenberg). The ideal postdoctoral fellow will have the opportunity to spend time at the labs of both of the PIs (in Toronto and Vancouver).

• a PhD in a quantitative discipline (computer science/ statistics or biostatistics is preferred) by the start of the postdoc
• expertise in machine learning, statistical learning or statistical analysis of high dimensional data
• a strong publication record (at least two published papers and one other in preparation)
• an interest in designing models and algorithms for solving biological problems
• experience with psychiatric genetics or genomics, or analysis of genetics and methylation data
• advanced knowledge of Python and R, and a scripting language (e.g., working with Unix shell) .

The position is for a duration of up to 3 years, renewed yearly. Compensation, including generous benefits, is competitive and commensurate with experience.

A complete application should include a statement of interest, a CV, and the names of 2 reference. Please submit applications to Sara Mostafavi, (saram@stat.ubc.ca) and Anna Goldenberg (anna.goldenberg@utoronto.ca) , with “Postdoctoral fellowship” in the subject line. The starting date of the position is October 1st, 2016. The position will remain open until filled.