We are looking for a highly motivated individual to work at the intersection of Big Data analysis, machine learning, and functional genomics, with opportunities for close collaborations with experimentalists and high-impact clinical researchers. Possible projects include developing algorithms and systems for chromatin and epigenetic modeling, heterogeneous data integration, understanding pathway dynamics and cell-lineage specificity, and neurogenomics. Ideal candidate would have a Ph.D. in Bioinformatics, Computer Science, Statistics, Mathematics, Engineering or a related field, and have a strong computational background. For exceptional computational candidates, extensive knowledge of biology is not required. This position will be based, and have a principal office or workspace, at the foundation, but have extensive interactions and, if desired, a associate affiliation with Princeton University.
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