Aviad Tsherniak

Background

About Aviad Tsherniak

out-of-date stuff below - How can a data scientist drive the discovery of new therapies for cancer patients? A major goal of cancer medicine is to be able to match each cancer patient with the most effective drug that would kill their tumor cells but not any normal cells (aka Precision Cancer Medicine). Cancer is a very heterogeneous disease, with each tumor (even within the same cancer type) harboring a different set of genetic aberrations that drives it and a different set of vulnerabilities that can be exploited therapeutically. At the Cancer Data Science group of the Broad Institute we use machine learning approaches to create a map of cancer vulnerabilities from loss-of-function screens (RNAi, CRISPR/Cas9, small molecules) across many cancer types (aka Cancer Dependency Map). We are building models that can predict the vulnerabilities of each tumor from its molecular characterizations (such as DNA and RNA sequences). This will allow both the matching of patients with the best therapy available, but also drive the development of new drugs that can exploit previously uncharacterized vulnerabilities. We’re hiring! Email me at [my first name] at broadinstitute dot org if you’re interested in joining us. Specialties: Machine learning, cancer genomics, predictive modeling, deep learning, matrix factorization, statistical inference, computational biology, multilevel modeling.