Sloan Kettering Institute (SKI) is excited to announce The Marie-Josée Kravis Fellowship in Quantitative Biology, a postdoctoral fellowship that aims to provide support to quantitative biologists focusing on high-risk, high-impact cancer research.
Demand for gifted quantitative biologists is high and spans across many industries. Furthermore, finding a quantitative biologist who specializes in cancer is even more difficult. The ability to efficiently navigate and analyze massive quantities of information can yield deep insights into how cancer grows and spreads — and how to fight it.
Computational biologists combine an understanding of intricate biological processes with expertise in quantitative approaches, data science, and algorithms. In the context of cancer research, they use advanced statistical, mathematical, and computing methods to simulate the behavior of living organisms from the molecular level up through the whole being, creating models that can make useful predictions about the development and behavior of cancer.
This award is designed to build a new generation of skilled quantitative biologists who specialize in cancer by recruiting and training top talent at MSK. Targeting quantitative scientists with training in mathematics, computer science, physics, engineering, or other related disciplines, this postdoctoral fellowship will promote innovation through a joint mentorship model in which a fellow is assigned to both a “dry” lab devoted to computational science and a “wet” one devoted to an area of cancer biology. This unique position will complement and strengthen MSK’s traditional laboratory and clinical research and open enormous potential for fellows to drive translational discovery.
Applications from internal and external candidates are now being accepted. For the current RFA, please click here.
Please contact Jessica Gotterer at [email protected] for questions.
Colorectal cancer (CRC) is the second most common cause of cancer death in the US and immune checkpoint therapy fails as a treatment in most cases. We hypothesize that this failure is linked to the activities and interactions of T cells, which are not yet well understood in the context of CRC. To address that, we will use high-throughput single-cell sequencing methods to analyze the roles of the different T cells that will potentially enable the development of therapies for this disease.
In collaboration with the Deasy/Tannenbaum Group and the Sarcoma Biology Laboratory, Dr. Weistuch has developed a new algorithm to reconstruct the accumulation of DNA copy number alterations (amplifications/deletions) within a tumor using statistical information gathered from many constituent cells. The approach, while general, has the potential to profoundly impact future treatment by revealing the driving events of liposarcoma, a type of cancer characterized by complex copy number alterations and poor patient outcomes.