RESPONSIBILITIES

• Participate in generating, processing and evaluating large oncology-related datasets.
• Work on a variety of high-dimensional data projects largely centered on biomarker discovery and develop biomarkers for response to therapy and disease subtype classification.
• Execute a wide range of computational and analytical tasks, including developing and implementing algorithms for target identification and biomarker discovery.
• Integrate publicly or commercially available genomic data with novel experimental data.
• Identify and execute innovations (computational, statistical, and strategic) that will quantifiably improve Projects.
• Identify new datasets and data mining techniques relevant to cancer target and drug discovery.
• Develop and test novel methods and algorithms, working with academic collaborators where opportunities arise.

REQUIREMENTS

• PhD in Biology, Bioinformatics, or equivalent
• Interest in, and working knowledge of cancer biology
• A solid understanding of statistics. Have experience with a broad range of statistical methods for classification and prediction, e.g., linear models, machine learning, and other multivariate analysis methods
• Programming experience and ability to write R and/or Perl script
• The candidate will have experience with large-scale genomics data and a solid understanding of bioinformatics data bases
• The candidate will have the ability and interest in learning new techniques and skills in accordance with evolving research program needs
• Candidates with a proven ability to work efficiently in a team setting, and excellent communication skills are preferred

LOCALE

HOW TO APPLY