Doctor of Philosophy in Biostatistics - Big Data Track

Program Summary

The biomedical research enterprise is increasingly becoming data-intensive and data-driven. Massive streams of data are being generated to interrogate biological systems and improve health care. Biomedical Big Data (BBD) is characterized by high dimensionality, complexity and diversity. It has become abundantly clear that effective statistical methodologies are essential for processing, analyzing and mining BBD. The Big Data Biostatistics program aims to train the next generation of data scientists, addressing regional and national demands for experts in statistical methods for BBD analysis.

The new track provides rigorous foundations in probability theory, statistics and computational sciences, combined with a broad knowledge of applications to biomedical research. The core curriculum consists of traditional Biostatistics coursework such as: Probability Theory, Mathematical Statistics, Linear Models and Multivariate Analysis; core computational competency coursework such as Design and Analysis of Algorithms, Database Design and Programming; and biomedical research oriented coursework such as: Functional Genomics, Bioinformatics, and Medical Informatics.

In consistency with the overall goals of the PhD program in Biostatistics, the new track has been designed to provide rigorous foundations in statistics and computational sciences, combined with a broad knowledge of applications to biomedical research. This is achieved by a mixture of both foundational courses in statistics, mathematics, and Biostatistics from the existing curriculum, as well as additional computer science, and application oriented core courses and electives included in the proposed curriculum. This will enable graduates of the Big Data Biostatistics Track of the PhD Program to take a full advantage of data driven revolution in biomedical sciences and the society at large.

PhD Biostatistics - Big Data Track Curriculum (PDF)

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Program Goals

Graduates of our PhD program track in Big Data will be able to:

• Conduct and publish original research in biostatistics and bioinformatics
• Work independently as a practicing biostatistician and bioinformaticians
• Teach biostatistics and bioinformatics to public health and medical professionals, to other scientists, and/or to undergraduate and graduate students