Research Scholar

Memorial Sloan; New York (NY); On-site; USD 77,591 - 85,000; Full time

Job summary

Memorial Sloan Kettering Cancer Center is seeking a postdoctoral researcher for the MSK Theory Group to apply quantitative training to cancer problems, collaborating with experimentalists and physician-scientists. Strong publication record and ability to interface across disciplines are essential.

Responsibilities include independence as a fellow, weekly chalk talks, and contributing to AI, ecology, and evolution projects; opportunity to work with leading labs and translational research teams.

Qualifications

• PhD in physics, mathematics, computer science, or related quantitative field with demonstrated output.
• Experience applying quantitative training to cancer-related problems.
• Strong publication record and ability to collaborate across disciplines.

Responsibilities

• Independence as a fellow and weekly chalk talks.
• Interface with experimentalists and physician-scientists to answer problems.
• Contribute to interdisciplinary research at the frontier of cancer, AI, ecology, and evolution.

Skills

Programming

Frontier modeling

Artificial intelligence

Interdisciplinary collaboration

Education

PhD in quantitative field

Tools

Data analysis

Job description

About Us:

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 pursueour missionat 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.

Key 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.

Preferred Skills:

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

Pay Range: $77,591 - $85,000

Pay Range: $0.00 - $10,000,000.00FSLA Status: Exempt

Closing

At MSK, we believe in fair, competitive pay that reflects your job, experience, and skills.

MSK is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status or any other factor which cannot lawfully be used as a basis for an employment decision.

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