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Tal Einav, PhD | Faculty Candidate Seminar
February 14 @ 4:00 pm - 5:00 pm
Please join us for the last Faculty Candidate Seminar on Tuesday, February 14th at 4:00 PM in 1131 Bioinformatics. Tal Einav, Ph.D. from Fred Hutchinson Cancer Research Center in Seattle will present talk title “Machine Learning the Rule of Antibody-Virus Interactions.”
Dr. Tal Einav earned his PhD at Caltech with Dr. Rob Phillips, whose lab specializes in developing models that don’t just fit data, but provide deep insights into the underlying mechanisms. In his postdoc, Dr. Einav shifted lanes into immunology, joining Dr. Jesse Bloom’s lab at the Fred Hutch Cancer Center which studies the antibody response against viruses such as influenza, HIV, and SARS-CoV-2. Dr. Einav is a Damon Runyon Quantitative Biology Fellow, and today we will hear about one of his multidisciplinary research projects that combines concepts from physics, math, biology, and computer science to help us understand and augment our antibody response against viruses.
130 Mason Farm Rd
Chapel Hill, North Carolina 27514
Abstract by Dr. Tal Einav: Immunology is undergoing a paradigm shift where the objective has expanded from creating a stopgap vaccine against a currently-circulating virus to developing a universal vaccine that confers lifelong protection. My research uses biophysical modeling and machine learning to probe how the antibody response changes with each viral exposure, with the ultimate goals of making the antibody response programmable and guiding it to a maximally-protective configuration. My lab will initially build off my expertise with influenza, but future efforts will generalize these methods to other viruses such as HIV-1 and SARS-CoV-2 that are of interest to public health.