One of the central challenges in genomics and medicine is to organize, analyze, and convey the rapidly growing datasets that inform on the genetic basis of disease.
The T2D-GENES Consortium is a National Institutes of Health funded, international collaborative effort to perform
(1) whole exome sequencing in 10,000 diabetes cases and controls of diverse ancestries and
(2) deep whole genome sequencing in 600 Hispanic pedigrees.
As a central goal, the Consortium seeks to build a Diabetes Genetics Portal to enable biologists and the broader community to access and interact with the human genetics data and results generated from this project. It is anticipated and desired that this effort will serve as a model and catalyst for creating a scalable platform and approach to convey such information for a wide array of diseases.
The widespread application of next-generation sequencing to human genetics has created a wealth of raw data for type 2 diabetes and other complex diseases. Our ability to interpret this data is limited by our ability to organize, integrate, and analyze it systematically as well as our ability to make results, both static and dynamic, accessible to a wide community.
Toward these ends, the successful candidate will design and implement pipelines and methods to analyze and interpret human genetics data for type 2 diabetes. They will work with end-users of a world-wide type 2 diabetes genetics portal to define and incorporate their requirements into these analyses. This work will not only serve as the analytical backbone of the diabetes portal but also serve as a model for other diseases as well.
KEY RESPONSIBILITIES / ESSENTIAL FUNCTIONS
- Will conceive and develop algorithms, implement pipelines, and methods to analyze and interpret human genetics data.
- Will apply computational techniques and genetics domain knowledge to design and implement analysis tools to solve complex computational and mathematical problems.
- Will rapidly prototype, using novel data sets, and then instantiate these methods into usable, robust, accessible software tools.
- Perform analysis and interpretation of large-scale genetic data sets.
- Contribute to and maintain shared, documented, and reusable codebases.
- Prepare written reports and presentations for internal use and publication
- Ph.D in life sciences, mathematics, computer science or a related field
- Must have significant programming and algorithm development experience and familiarity with biological research problems.
- Must have track record of high-quality computational research.
- Must possess extensive experience with Java (or C/C++), and familiarity with Python (or Perl), and analysis tools like MATLAB and/or R.
- Excellent oral and written communication skills required.
- Must be able to work collaboratively with other scientists on computational research in a fast-paced environment.
- Must enable the research of other program scientists through excellent communication, teamwork, and a focus on creating usable and accessible research software tools.
- Must be capable of working in an interactive team environment while conducting self-directed research within broader goals set by group.
To apply for this position, please CLICK HERE