The Perelman School of Medicine at the University of Pennsylvania invites applications for the position of Chair of the DBEI. 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. Read about our teaching approach. The DBEI is an international leader in biostatistics, epidemiology and informatics; its faculty collaborates with biomedical researchers throughout the University. 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. 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. Professor of Biostatistics That is why this department has put forward a bold vision in population-health science: a single academic home for biostatistics, epidemiology and informatics. Members of the biostatistics faculty lead research that develops novel statistical-methods approaches to meet complex data challenges across many domains. Read about our latest findings. Bhaswar B. Bhattacharya; Andreas Buja; Tony Cai; Jian Ding MORE, © 2019 Trustees of the University of Pennsylvania. Read about our latest findings. 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. J. Richard Landis, Ph.D. Standing. mjoffe@mail.med.upenn.edu. How can we now estimate causal effects, properly adjusting for confounding and bias? And they contribute as team scientists to investigations across many disciplines. MORE Read the professional-life stories of our biostatistics faculty. | 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. All rights reserved. That is why this department has put forward a bold vision in population-health science: a single academic home for biostatistics, epidemiology and informatics. Biostatistics faculty and students at Penn are involved in biostatistical methodological research spanning many intellectually diverse areas. 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. They design and conduct national, multi-center clinical trials and direct clinical-research networks. Members of the biostatistics faculty lead research that develops novel statistical-methods approaches to meet complex data challenges across many domains. Biostatistics Members of the biostatistics faculty lead research that develops novel statistical-methods approaches to meet complex data challenges across many domains. 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. Learn more about the position (link is external). Our response to COVID-19: roundup of learning resources, news, published research. And they contribute as team scientists to investigations across many disciplines. Faculty Index. How can we accurately portray the associations between exposure and disease in the era of “big data” and “precision medicine”?
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