We are looking for motivated individuals 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 candidates 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 Simons Foundation in New York City, but have extensive interactions and, if desired, an associate affiliation with Princeton University.

To apply, send a CV including three references to Olga with the email subject line ‘Postdoctoral Application’.

We are open to working with motivated students at all levels (PhD, masters, undergraduate). Fostering a collaborative environment is central to our lab. We help students develop a personal understanding of biology while cultivating the strong computational mindset required for quantitative analysis. Current Princeton students should contact Olga via e-mail and include a brief overview of their background and research interests.

Prospective PhD students are encouraged to apply to any of the following programs at Princeton University: