● This research position is aimed at postdocs who are specifically looking to apply their theoretical training to problems in cancer and have a demonstrated record of quantitative training applied to problems in biology, including using and developing frontier methods in artificial intelligence.
● The project scope requires a strong desire to derive quantitative insights from unique data and interface directly with experimentalists and physician-scientists to answer some of the toughest problems in biology.
● A successful candidate will have considerable independence as a fellow, participate in weekly chalk talks, and interact with aligned investigators in the Greenbaum and other labs.
· PhD in physics, mathematics, computer science, or other quantitative research discipline with demonstrated theoretical research output.
· Demonstrated strong expertise in frontier modeling concepts in a related field.
· Experience in programming, with a desire to learn about computational analysis of biological data towards predictive models.
· Track record of exceptional publications.
· Ability to draw connections between disparate disciplines (as demonstrated through publications, presentations, talks, funding sources).
· Ability to work collaboratively in a multidisciplinary team environment.