[Next-Generation Sequencing Book]
  • [Photo] Daniele Merico • September 2, 2010

    BACKGROUND

    Genome-scale experiments, such as SNP or gene expression microarrays, typically lead to the identification of large gene-lists. The interpretation of results and the formulation of consistent biological hypotheses from these large lists are challenging. Computational approaches can aid interpretation by relating the gene lists to knowledge about the biological system, such as known pathways. This computational analysis can be used to generate hypotheses that can be experimentally tested.

    RESPONSIBILITIES

    The applicant will work with multiple investigators in a large-scale cancer stem cell program to provide bioinformatics analysis of cancer genomics data, including gene expression, copy number variation, and sequence data derived from animal cancer models and patient samples.

    REQUIREMENTS

    • The applicant will have a PhD in molecular biology, molecular genetics, computational biology, bioinformatics or a related discipline.
    • Evidence of excellent communication and teamwork skills is essential.
    • A solid knowledge of basic statistics (hypothesis testing, multiple correction, normalization, clustering) is also required.

    PREFERENCES

    • Previous experience in experimental biology research, microarray data analysis (e.g. pathway analysis, GSEA, Cytoscape) and R programming will be favored in applicant selection.
    • Programming skill in other languages such as Matlab, Perl, Python or Java is a plus.

    LOCALE

    The work will be conducted at the University Health Network and the University of Toronto, a major international centre of genomics, proteomics and systems biology research, in the heart of Toronto. There will ample opportunity for professional development through research seminars, workshops and research in progress meetings.

    HOW TO APPLY

    Please send your CV and the names of 3 references to gary.bader[at]utoronto.ca

    LINKS

    http://baderlab.org

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