We seek a postdoctoral fellow to develop novel integrative approaches for the identification of molecular predictors of response to approved and experimental drugs for breast and brain cancers. We have generated high-dimensional molecular (mutations, copy number variations, transcriptomics, epigenomics) and pharmacological (drug sensitivity) profiles of a large panel of breast and brain cancer cell lines. A well established patient-derived xenograft platform provides a unique opportunity to explore the biology underlying drug response, and develop predictors that can be validated in vivo before their use in clinical trials.
Required qualifications Doctorate in computational biology, computer science, engineering, statistics, applied mathematics, or physics. Published/submitted papers in cancer genomics and/or machine learning research. Experience with analysis of high-throughput omics data, such as next-generation sequencing and gene expression microarrays, in cancer research. Very strong expertise in programming and machine learning (R, C/C++, Python and Unix programming environments).
Preferred qualifications Hands-on experience in high performance computing, especially for parallelizing code in C/C++ (openMP) and/or R in a cluster environment (e.g., Sun Grid Engine/Torque).
How to apply Submit a CV, a copy of your most relevant paper, and the names, email addresses, and phone numbers of three references to email@example.com. The subject line of your email should start with “POSTDOC PRED2 -- BHKLAB”. All documents should be provided in PDF.
Deadline Applications must be submitted before Dec 1st 2017.
Team The candidate will work in a large multidisciplinary team of 8 laboratories from the Princess Margaret Cancer Centre as part of Terry Fox New Frontiers Research Project:
- Benjamin Haibe-Kains: https://www.pmgenomics.ca/bhklab/
- Cheryl Arrowsmith: http://nmr.uhnres.utoronto.ca/arrowsmith/
- David Cescon: https://www.uhnresearch.ca/researcher/david-cescon
- Lillian Siu: https://www.uhnresearch.ca/researcher/lillian-l-siu
- Linda Penn: http://pennlab.ca/
- Mathieu Lupien: https://www.pmgenomics.ca/lupienlab/
- Pamela Ohashi: http://www.immunology.utoronto.ca/content/pamela-ohashi
- Trevor Pugh: http://medbio.utoronto.ca/faculty/pugh.html
Dr. Haibe-Kains’ lab will host the candidate. Dr. Haibe-Kains has over 10 years of experience in computational analysis of genomic and transcriptomic data, in the context of translational research. He is the (co-)author of more than 120 peer-reviewed articles in top bioinformatics and clinical journals. For an exhaustive list of publications, go to Dr. Haibe-Kains’ Google Scholar Profile.
Princess Margaret Cancer Centre The Princess Margaret Cancer Centre (PM) is one of the top 5 cancer centres in the world. PM is a teaching hospital within the University Health Network and affiliated with the University of Toronto, with the largest cancer research program in Canada. This rich working environment provides ample opportunities for collaboration and scientific exchange with a large community of clinical, genomics, computational biology, and machine learning groups at the University of Toronto and associated institutions, such as the Ontario Institute of Cancer Research, Hospital for Sick Children and Donnelly Centre.