A once-in-a-lifetime opportunity to make fundamental contributions to The Cancer Genome Atlas, a project of national policy significance and global impact in the search for a cure to cancer. Interact with world-class researchers throughout Boston and the nation, operating and extending our Genome Data Analysis Center pipelines; with an emphasis upon data aggregation (from national and international portal sources) and processing, and the development of automatable software, processes, standards, and documentation for such.
As appropriate, GDAC duties would include:
- Track and coordinate data & algorithmic modules in pipeline runs
- Perform investigative forensics upon data & algorithms
- Integrate support for new genomic data types as needed
- Integrate new genomic analysis modules as needed
- Extend and/or refactor existing software infrastructure
- Assist in the creation of new infrastructure
- Help grow our corpus of documentation
- Participate in TCGA analysis working groups and telecons
- Proactively identify technical hurdles and recommend solutions
- Collaborate with other engineers on process or design issues
- Provide reliable time estimates for assignments
- Other related tasks as required by pipeline manager
- Bachelor’s degree required, preferably in Computer Science or Bioinformatics, and 3-5 years of software development experience.
- Bachelor’s degrees in Biology will be considered if there is strong evidence of coding skill.
- Strong programming skills required in at least two of the following languages: Python, Java, Matlab, R, Perl, C/C++, PHP, Unix shell (BASH)
- Knowledge of LSF, Sun Grid Engine, GenePattern, Galaxy, Oracle, SQL, HTML are all a big plus.
- Prior involvement or interest in biology or genomics domain a plus.
- Excellent communication skills and the ability to perform effectively in a fast paced environment required.
- Must be able to handle a variety of tasks, effectively solve problems with numerous and complex variables, and be able to shift priorities rapidly, and operate with minimal supervision.
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