Research Scholar

Memorial Sloan Kettering Cancer Center • New York, NY

3d

About The Position

The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe. The MSK Theory Group is a new initiative to recruit advanced quantitative scientists to conduct interdisciplinary research at the frontier of cancer, immunology, artificial intelligence, ecology, and evolution in close collaboration with world-class experimentalists and physician-scientists at Memorial Sloan Kettering Cancer Center. 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.

Requirements

• 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.

Nice To Haves

• Some experience working with biological data
• Strong interest in translational research and collaboration with clinical teams

Responsibilities

• Apply theoretical training to problems in cancer.
• Derive quantitative insights from unique data.
• Interface directly with experimentalists and physician-scientists to answer tough problems in biology.
• Participate in weekly chalk talks.
• Interact with aligned investigators in the Greenbaum and other labs.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree