Read about our teaching approach. The Graduate Group in Epidemiology and Biostatistics (GGEB) is responsible for developing and administering the PhD degree programs in epidemiology and biostatistics as well as the MS program in biostatistics.
The DBEI is an international leader in biostatistics, epidemiology and informatics; its faculty collaborates with biomedical researchers throughout the University. They design and conduct national, multi-center clinical trials and direct clinical-research networks. That is why this department has put forward a bold vision in population-health science: a single academic home for biostatistics, epidemiology and informatics. J. Richard Landis, Ph.D. How can we accurately portray the associations between exposure and disease in the era of “big data” and “precision medicine”? Read about our latest findings. Our response to COVID-19: roundup of learning resources, news, published research. Read the professional-life stories of our biostatistics faculty. Professor of Biostatistics

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To understand health and disease today, we need new thinking and novel science —the kind we create when multiple disciplines work together from the ground up. | Disclaimer, Video: Advancing the Full Spectrum of Population-Health Science, Toward a New Research-Practice Paradigm: Keynote by Peter J. Embi, DBEI & CCEB Research Day: Division Leader Videos, Research Day Keynote: Michael V. McConnell Video, Distinguished Faculty Reach Across Disciplines, Partnering to Address Psoriatic Arthritis, Looking to a Collaborative Approach to Advance MS Solutions, Working Across Disciplines to Understand Sex Differences in Concussion. MORE

Members of the biostatistics faculty lead research that develops novel statistical-methods approaches to meet complex data challenges across many domains. And they contribute as team scientists to investigations across many disciplines. Members of the biostatistics faculty lead research that develops novel statistical-methods approaches to meet complex data challenges across many domains. mjoffe@mail.med.upenn.edu. All rights reserved. The Perelman School of Medicine at the University of Pennsylvania invites applications for the position of Chair of the DBEI. Bhaswar B. Bhattacharya; Andreas Buja; Tony Cai; Jian Ding Moreover, our faculty members have won singular international recognition for their contributions to many parts of statistical science including observational studies, statistical algorithms, game theory, high dimensional inference, information theory, nonparametric function estimation, model selection, time series analysis, machine learning, and probability theory. Biostatistics Members of the biostatistics faculty lead research that develops novel statistical-methods approaches to meet complex data challenges across many domains. That is why this department has put forward a bold vision in population-health science: a single academic home for biostatistics, epidemiology and informatics.

Learn more about the position (link is external). Areas of research include Bayesian methods, causal inference, clinical trials, clustered data, longitudinal data analysis, missing data, imaging, statistical genetics and bioinformatics, survival analysis, and survey research. Biostatistics faculty and students at Penn are involved in biostatistical methodological research spanning many intellectually diverse areas. How can we now estimate causal effects, properly adjusting for confounding and bias? And they contribute as team scientists to investigations across many disciplines. Faculty Index. Read about our latest findings. The Graduate Group in Epidemiology and Biostatistics (GGEB) is responsible for developing and administering the PhD degree programs in epidemiology and biostatistics as well as the MS program in biostatistics. To understand health and disease today, we need new thinking and novel science —the kind  we create when multiple disciplines work together from the ground up. Such questions inspire our faculty members as they educate the next generation of leaders in biostatistical theory, methods and practice. Standing.

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