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See how our current work and research is bringing new thinking and new solutions to some of today's biggest challenges.

Graduate Field of Computational Biology

Tackle research using real world data

    The graduate field of Computational Biology offers Ph.D. degrees in the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological systems.

    The field provides interdisciplinary training and research opportunities in a range of subareas of computational biology including comparative and functional genomics, systems biology, molecular and protein networks, population genomics and genetics, bioinformatics, model system genomics, agricultural genomics, and medical genomics.

    Doctor of Philosophy (Ph.D.)

    Computational Biology (CB) at Cornell is an interdisciplinary program that links the computational and mathematical sciences with the life sciences. Quantitative prediction and interpretation are becoming increasingly essential components of biology and other fields. Complex patterns, structures and interactions raise fundamental and fascinating questions that can only be addressed using formal mathematical, statistical, and computational methods.

    The wealth of data being acquired to address these questions requires new and substantive quantitative approaches to make possible appropriate analysis and interpretation. The unprecedented level of computational power now available to researchers provides the means for increasingly sophisticated analyses of highly complex systems arising in the biological sciences.

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    More about Computational Biology
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    Kaixiong Ye, postdoctoral associate, explains a model in the Department of Biological Statistics and Computational Biology.

    Explore your opportunities

    A CALS education goes beyond the classroom and gives students frequent opportunities to apply what they learn in real-world settings.