Скачать или смотреть Modelling the Accumulation of Mutations During Cancer Progression without Explicit Time

Presented By: Rebekka Burkholz, PhD

Speaker Biography: Rebekka Burkholz holds a tenure-track faculty position at the Helmholtz Center for Information Security (CISPA) in Germany. The big goal of her research is to make deep learning useful in setting of small sample size and large noise, as it is common in biomedical applications. She recently was a PostDoc at the Biostatistics Department of the Harvard T.H. Chan School of Public Health, where she worked with John Quackenbush. Before that, she enjoyed postdoctoral research at ETH Zurich at the Institute for Machine Learning and earned her PhD with Frank Schweitzer at the Chair of Systems Design. Her Phd thesis on systemic risk at the ETH Risk Center won the Zurich Dissertation Prize and her work on international maize trade received the CSF Best Contribution Award. She studied Mathematics and Physics at TU Darmstadt.

Webinar: Modelling the Accumulation of Mutations During Cancer Progression without Explicit Time

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