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Opportunity: Postdoctoral fellowships in cancer computational biology @ Princess Margaret Cancer Centre -- Toronto, Canada
Submitted by Benjamin Haibe-Kains; posted on Thursday, April 03, 2014
The Bioinformatics and Computational Genomics Laboratory at the Princess Margaret Cancer Centre (Toronto, Ontario, Canada) seeks postdoctoral fellows to work on research projects in computational genomics and machine learning.

Our research focuses on the development of novel computational approaches to best characterize carcinogenesis, drug mechanisms of action and therapeutic potential from high-throughput genomic data. We have strong expertise in prognostic and predictive biomarkers in cancer and drug repurposing. Our large network of national and international collaborators, including clinicians, molecular biologists, engineers, statisticians and bioinformaticians, uniquely position us to perform cutting-edge translational research to bring discoveries from bench to bedside.

We seek postdoctoral fellows for several projects in cancer computational biology. Selected projects include:
1. Large-scale integration of pharmacogenomic data to develop robust predictors of drug response.
2. High-throughput drug repurposing and rational discovery of drug synergy from pharmacogenomic data.
3. Modeling of co-dependencies between tumor cells and their microenvironment, and selection of drugs to inhibit these interactions.
4. Integrative analysis of multiple omics data types (DNA, mRNA, miRNA, proteomics) to develop the next generation of subtyping and prognostic models in breast, ovarian, H&N and pancreatic cancers.

Lab director:
Dr. Benjamin Haibe-Kains, has 10 years of experience in computational analysis of genomic data, including genetic and transcriptomic data. He is the (co-)author of more than 70 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 is a teaching hospital within the University Health Network and affiliated with the University of Toronto. It has 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 Hospital for Sick Children and the Donnelly Centre.

Doctorate in computational biology, computer science, engineering, statistics, or physics. Published/submitted papers in genomics or machine learning research. Experience with analysis of high-throughput omics data, such as next-generation sequencing and gene expression microarrays, in cancer research. Expertise in R, C/C++ and Unix programming environments.

Hands-on experience in high performance computing, especially for parallelizing code in C/C++ (openMP) and/or R in a cluster environment (Sun Grid Engine).

We will accept applications until the position is filled. Please submit a CV, a copy of your most relevant paper, and the names, email addresses, and phone numbers of three references to benjamin.haibe.kains[at] The subject line of your email should start with "POSTDOC BHKLAB". All documents should be provided in PDF.

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