Ph.D. in Computational Mathematics, Science and Engineering
Applications for Fall 2026 are now open! Application deadline is January 2nd. Learn how to apply via link.
If you would like to be considered for departmental, college, and University fellowships, submit all materials (including transcripts and recommendation letters) by January 2nd.
If you have questions, please contact the CMSE Graduate Director at cmsegrad@msu.edu.
The CMSE Ph.D. program gives students concrete and broad training in computational
mathematics and its applications to solve the challenging problems in science, engineering,
health, education, and other domains. As a unique advantage, this Ph.D. program prepares
the future field leaders with in-depth knowledge in computational mathematics and
science. The students will systematically learn the cutting-edge theories/methodologies
and techniques in scientific computing, data science, and artificial intelligence
(AI), and will be able to advance scientific discoveries and engineering paradigms
via synergistic inter-disciplinary research projects. A highly vibrating and engaging
ecosystem with collaboration opportunities is provided in this graduate training to
foster rigorous and impactful research innovations.
Students that have completed this Ph.D. program will conduct original research and
present in peer-reviewed publications, along with other venues of scientific communications,
to gain solid expertise in the following:
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Formulate scientific and engineering problems into new mathematical models and develop robust, scalable algorithms with rigorous theoretical foundations to gain novel insights and knowledge.
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Establish data-driven modeling and analysis frameworks empowered by big-data integration, machine learning, and AI, grounded in strong theoretical understanding of algorithmic principles.
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Harness AI and high-performance computing to advance large-scale simulations and accelerate discoveries in science and engineering.
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Foster interdisciplinary applications that enable breakthroughs across science and engineering.
Mathematical Foundations of Computational Science
- Numerical analysis
- Computational harmonic analysis
- Mathematical modeling
- Computational physics
- Inverse problem
Computational Data Science & AI
- Scientific machine learning
- High performance computing
- Topological data analysis
- Computational biology
- Statistical modeling