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DESCRIPTION

A highly motivated individual is sought to lead bioinformatics projects in tumor genomics. The group is a part of an interactive environment in Cancer Research at Abbott, where scientific innovation and creativity are highly valued.
The successful candidate will contribute to genomic biomarker discovery and target identification in cancer by performing analyzes of genomic data obtained internally or from public and private databases. A particular focus will be on the acquisition and analysis of high-resolution array CGH data to identify genomic correlates of cancer initiation, progression, and response to drugs. The incumbent will be expected to routinely evaluate new software tools and genomic databases. Additionally, he/she will be involved in the analysis of other high-throughput genomic data, such as gene expression signatures, promoter methylation, microRNA expression, and mutation patterns, to enable integrative studies in cancer drug discovery and support multiple drug discovery projects. The successful candidate will regularly interact with multiple drug discovery teams within Cancer Research.
Because manipulation of genomic data requires continuous software acquisition/development, the ability to create and maintain the computational environment for data analysis will be a strong plus.

May hire at grade 18: Assoc Research Investigator or grade 19: Research Investigator depending on skills and experience.

Qualifications:
Required qualifications:
· PhD with training in bioinformatics, computational biology or related fields
· Demonstrated experience in genomic data mining
· Strong knowledge of statistics (pattern recognition, class discovery, clustering, outcome prediction, etc)
· Programming expertise is a strong plus
· Excellent organizational, time management, communication, and interpersonal skills

Abbott welcomes and encourages diversity in our workforce. EEO/AA

For immediate consideration, please apply online at:

http://appclix.postmasterlx.com/track.html?pid=402881bd161e1efc011621226d8e0b5b&source=bioinformatics