Postdoctoral Associate- Computational Biology

We are looking for a post doctoral associate in Computational Biology to join the 'Learning from Human Genetics' initiative within the Program of Medical and Population Genetics at the Broad Institute. Our goal is to develop and apply methods to understand the function of genes/genetic loci identified in genome-wide association studies for Crohn's disease (CD) and Type 1 diabetes (T1D).

The ideal candidate will have an interdisciplinary background in mammalian physiology and bioinformatics/computational biology, particularly in the analysis and interpretation of expression data, proteomics data, and working knowledge of statistical methods, the reconstruction of signaling networks, computational network inference from experimental expression data, and the integration of public data sources and biology ontology to enable systems biology research.

Prospective applicants should have made significant contributions to their area of study, as evidenced by a strong publication record in high-impact journals. The computational biologist will design, implement, and apply novel machine-learning algorithms to integrate various sources of genomic data to reconstruct genetic regulatory networks and to predict the function of disease-associated genes.
Requirements:
Qualified candidates should have:

- A Ph.D. in computational biology, computer science, engineering, mathematics, physics, or related field

- Ability to program in Perl or Python, with knowledge of R/S-plus/ MATLAB and SQL essential

- Familiarity with Unix systems

- Demonstrated applied bioinformatics/computational proficiency as evidenced by relevant publications in peer-reviewed journals.

We are seeking creative and highly motivated individuals who want to work in a dynamic, multi-disciplinary research environment.