Biomedical Data Science and Informatics, M.S. / Ph.D.
The nation’s transition to new healthcare delivery models and the exponential growth in biomedical data translate to a need for professionals with expertise in data science focused on biomedical research who can leverage big data to improve health in the state and the nation. Specialized tracks will initially include precision medicine, population health, and clinical and translational informatics.
Biomedical data science and informatics is an interdisciplinary field that applies concepts and methods from computer science and other quantitative disciplines together with principles of information science to solve challenging problems in biology, medicine and public health.
The BDSI program is a unique collaboration that brings together Clemson’s strengths in computing, engineering, and public health and MUSC’s expertise in biomedical sciences to produce the next generation of data scientists, prepared to manage and analyze big data sources from mobile sensors to genomic an imaging technologies. Graduates will possess marketable skills for informatics careers in biology, medicine or public health focused on the development of prescriptive analytics from large data sources and are well prepared to lead research programs in academic, healthcare, public health, and industry.
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The Master of Science Degree
This interdisciplinary program leverages the broad strength at Clemson spanning computing, engineering, mathematics, biology, public health, and other areas to produce the next generation of data scientists, prepared to manage and analyze big data sources from mobile sensors to genomic and imaging technologies. Graduates will possess the necessary skills for informatics careers in biology, medicine or public health focused on the development of prescriptive analytics from large data sources.
The program is designed for students with undergraduate computer science, math, engineering, or biomedical sciences backgrounds who wish to contribute to biomedical sciences or individual and societal health.
Highly qualified Clemson undergraduates who are interested in earning the M.S. in Biomedical Data Science and Informatics may begin earning their master’s degree while simultaneously completing their bachelor’s degree in Health Science. Learn more about the accelerated B.S. to M.S. program.
The M.S. and Ph.D. programs are a joint venture between Clemson University and the Medical University of South Carolina.
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The Doctor of Philosophy Degree
This interdisciplinary program leverages the broad strength at Clemson spanning computing, engineering, mathematics, biology, public health, and other areas to produce the next generation of data scientists, prepared to manage and analyze big data sources from mobile sensors to genomic and imaging technologies. Graduates will possess the necessary skills for informatics careers in biology, medicine or public health focused on the development of prescriptive analytics from large data sources to improve health in the state and the nation.
This program in unique to South Carolina and very few programs nationally focus on data science applied to the health and biomedical fields. Specialized tracks include precision medicine, population health, and clinical and translational informatics.
Graduates will possess marketable skills for informatics careers in biology, medicine, or public health focused on the development of prescriptive analytics from large data sources and will be prepared to lead research programs in academic, healthcare, public health, and industry. These specially trained scientists will be critical to on-going efforts to improve health outcomes in South Carolina and the nation.
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Contact Us
This degree program is located in the School of Computing located at 100 McAdams Hall. For more information, contact:
Dr. Aaron Masino
Associate Professor
School of Computing
Clemson University
315 McAdams Hall
amasino@clemson.eduAdam Rollins
Graduate Student Services Coordinator
School of Computing
Clemson University
rollin7@clemson.edu
864-656-5853
